(19)
(11)EP 3 264 364 B1

(12)EUROPEAN PATENT SPECIFICATION

(45)Mention of the grant of the patent:
22.04.2020 Bulletin 2020/17

(21)Application number: 16848160.4

(22)Date of filing:  23.09.2016
(51)International Patent Classification (IPC): 
G06T 7/00(2017.01)
G06T 7/579(2017.01)
(86)International application number:
PCT/CN2016/099925
(87)International publication number:
WO 2017/050279 (30.03.2017 Gazette  2017/13)

(54)

METHOD AND APPARATUS FOR OBTAINING RANGE IMAGE WITH UAV, AND UAV

VERFAHREN ZUR TIEFENBILDERFASSUNG FÜR UNBEMANNTES LUFTFAHRZEUG, VORRICHTUNG SOWIE UNBEMANNTES LUFTFAHRZEUG

PROCÉDÉ D'ACQUISITION D'IMAGE DE PROFONDEUR DE VÉHICULE AÉRIEN SANS PILOTE, DISPOSITIF ET VÉHICULE AÉRIEN SANS PILOTE


(84)Designated Contracting States:
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

(30)Priority: 25.09.2015 CN 201510628505

(43)Date of publication of application:
03.01.2018 Bulletin 2018/01

(73)Proprietor: Guangzhou Xaircraft Technology Co., Ltd.
Guangzhou, Guangdong 510000 (CN)

(72)Inventor:
  • CHEN, Yousheng
    Guangzhou, Guangdong 510000 (CN)

(74)Representative: Roider, Stephan et al
Pfarrer-Erhard-Weg 19
82008 Unterhaching
82008 Unterhaching (DE)


(56)References cited: : 
EP-A1- 2 849 150
CN-A- 103 426 200
CN-U- 202 075 794
CN-A- 102 749 071
CN-A- 105 225 241
  
  • MADJIDI H ET AL: "Vision-based positioning and terrain mapping by global alignment for UAVs", ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE, 2003. PROCEEDINGS. IEEE CONFERENCE ON 21-22 JULY 2003, PISCATAWAY, NJ, USA,IEEE, 21 July 2003 (2003-07-21), pages 305-312, XP010648399,
  • CHUNSUN ZHANG ET AL: "An Unmanned Aerial Vehicle-Based Imaging System for 3D Measurement of Unpaved Road Surface Distresses 1 : UAV-based imaging system for road distress measurements", COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, vol. 27, no. 2, 21 July 2011 (2011-07-21), pages 118-129, XP55472936,
  • BERND GIROD ET AL: "A NEW METHOD FOR SIMULTANEOUS ESTIMATION OF DISPLACEMENT, DEPTH, AND RIGID BODY MOTION PARAMETERS", 9TH IMDSP WORKSHOP, BELIZE, 1 March 1996 (1996-03-01), XP55472937,
  • M.J. WESTOBY ET AL: "'Structure-from-Motion' photogrammetry: A low-cost, effective tool for geoscience applications", GEOMORPHOLOGY, vol. 179, 1 December 2012 (2012-12-01), pages 300-314, XP055398584, AMSTERDAM, NL
  • ANUAR AHMAD: "Digital Mapping Using Low Altitude UAV", PERTANIKA J. SCI. & TECHNOL, vol. 19, 1 January 2011 (2011-01-01), pages 51-58, XP55472941,
  • LEE, D. ET AL.: 'Depth Estimation for Image-Based Visual Servoing of an Under-Actuated System' JOURNAL OF INSTITUTE OF CONTROL, ROBOTICS AND SYSTEMS vol. 18, no. 1, 31 December 2012, ISSN 1976-5622 pages 42 - 46, XP055370647
  • M.J. Westoby ET AL: "'Structure-from-Motion' photogrammetry: A low-cost, effective tool for geoscience applications", Geomorphology, vol. 179, 1 December 2012 (2012-12-01), pages 300-314, XP055398584, AMSTERDAM, NL ISSN: 0169-555X, DOI: 10.1016/j.geomorph.2012.08.021
  • CLEMENS HOLZMANN ET AL: "Measuring Distance with Mobile Phones Using Single-Camera Stereo Vision", 32ND IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS WORKSHOPS, IEEE, 18 June 2012 (2012-06-18), pages 88-93, XP032217932,
  
Note: Within nine months from the publication of the mention of the grant of the European patent, any person may give notice to the European Patent Office of opposition to the European patent granted. Notice of opposition shall be filed in a written reasoned statement. It shall not be deemed to have been filed until the opposition fee has been paid. (Art. 99(1) European Patent Convention).


Description

FIELD



[0001] The present disclosure relates to the technical field of image processing, and more particularly, to a method and an apparatus for obtaining a range image with an unmanned aerial vehicle (UAV), and an unmanned aerial vehicle.

BACKGROUND



[0002] In conventional imaging ways, a three-dimensional image model is converted into a two-dimensional gray-scale image and depth information of the image is lost during the imaging process. However, the depth information of the image is very important for subsequent applications (such as a 3D reconstruction, a geography mapping, etc.), so that it is significant to obtain a range image (or a depth map) for both theoretical research and engineering practice.

[0003] There are two kinds of ways to obtain the range image in the related art: active acquisition methods and passive measurement methods. In the active acquisition methods, energy such as laser, electromagnetic wave, ultrasonic wave, etc. may be actively emitted, and then reflected by an obstacle and then the reflected energy is received. The passive measurement methods are based on machine vision, such as binocular vision.

[0004] Currently, methods for obtaining the range image with a UAV usually include emitting an energy beam actively, detecting returned energy, and calculating the range image according to the detected energy. However, these methods are influenced susceptibly by surrounding environments, for example light may influence laser. In addition, these methods require that an object to be measured must be able to reflect the energy. When most of the emission energy is absorbed, it will lead to a failure. Moreover, a measurable range of these methods is limited because the emitted energy will be attenuated in the atmosphere. When a distance is too far, the attenuation will be so serious that the depth information cannot be measured accurately. On the other hand, the binocular vision method requires two cameras, and there must be a certain distance between the two cameras. The longer the distance to be measured, the greater the distance between the two cameras needs to be. For a small UAV, this will increase its load, and a maximum distance between the two cameras is limited, too because of the limited space of the small UAV.

[0005] Madjidi H. et al: "Vision-based positioning and terrain mapping by global alignment for UAVs" (ADVANCED VIDEO AND SIGNAL BASED SURVELLANCE, 2003. PROCEEDINGS. IEEE CONFERENCE ON 21-22 JULY 2003, PISCATAWAY, NJ, USA, IEEE, pages 305-312) relates to construction of 3-D topographic maps from stereo or monocular video, over coverage areas of kilometer scale, taken by low-altitude airborne platforms.

SUMMARY



[0006] The present application relates to a method for obtaining a range image with an unmanned aerial vehicle UAV according to independent claim 1 and an apparatus for obtaining a range image with an unmanned aerial vehicle UAV according to independent claim 6. Further aspects of the present application are defined by the dependent claims.

[0007] Additional aspects and advantages of embodiments of the present disclosure will be given in part in the following descriptions, become apparent in part from the following descriptions, or be learned from practice of embodiments of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS



[0008] The above and/or other aspects and advantages of the present disclosure will become apparent and more readily appreciated from the following descriptions of the embodiments with reference to the drawings, in which,

Fig. 1 is a flow chart illustrating a method for obtaining a range image with a UAV according to an embodiment of the present disclosure.

Fig. 2 is a schematic diagram illustrating a model for obtaining a range image with a UAV according to an embodiment of the present disclosure.

Fig. 3 is a block diagram illustrating an apparatus for obtaining a range image with a UAV according to an embodiment of the present disclosure.


DETAILED DESCRIPTION



[0009] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings, wherein the same or similar elements and the elements having same or similar functions are denoted by like reference numerals throughout the descriptions. Embodiments described herein with reference to drawings are explanatory, serve to explain the present disclosure, and are not construed to limit embodiments of the present disclosure.

[0010] A method for obtaining a range image with an unmanned aerial vehicle (UAV) and a UAV according to embodiments of the present disclosure will be described with reference to accompanying drawings as follows.

[0011] Fig. 1 is a flow chart illustrating a method for obtaining a range image with a UAV according to an embodiment of the present disclosure. As illustrated in Fig. 1, the method may include following s.

[0012] At block S1, an image sequence of a predetermined scene collected by an airborne camera of the UAV is read out, in which the Nth image and the (N+1)th image of the image sequence have an overlapping region, and a ratio of an area of the overlapping region to an area of the Nth image or a ratio of the area of the overlapping region to an area of the (N+1)th image is greater than a preset ratio. In other words, the image sequence of an object to be measured captured or taken by the airborne camera of the UAV is read out and two continuous images are extracted therefrom, for example, the Nth image and the (N+1)th image. Besides, the Nth image and the (N+1)th image must have the overlap region. To insure accuracy of a following optical flow calculation, the ratio of the area of the overlapping region to the area of the Nth image or the (N+1)th image needs to be greater than the preset ratio. More particularly, in an example of the present disclosure, for example, the preset ratio is 60%, that is, the area of the overlapping region accounts for more than 60% of the area of the Nth image or the (N+1)th image.

[0013] In addition, in an example of the present disclosure, to insure qualities of images taken by the airborne camera and to reduce disturbance to the following optical flow calculation that may be caused by airframe vibrations of the UAV, the airborne camera may be installed onto the UAV through a self-stabilizing platform, for example, as illustrated in Fig. 2. Meanwhile, to reduce influence of distortion of the image itself taken by the camera, a visual angle of the airborne camera cannot be too large. In an example of the present disclosure, the visual angle of the airborne camera is selected to be less than a preset angle. More particularly, for example, the preset angle may be 60 degree, as illustrated in Fig. 2. Obviously, the preset angle is not limited to the above angle and may be selected according to requirements of an actual scene (for example, the preset angle may be less than 60 degree), and this example is just illustrated as an example.

[0014] Furthermore, in some examples, as mentioned above, when the distortion of the image taken by the airborne camera is serious, the distortion of images in the image sequence must be adjusted so as to make the distortion in a tolerable range for following operations.

[0015] At block S2, for each pixel point in the overlapped region, position changing information of the pixel point in the (N+1)th image with respect to the Nth image is obtained, and a pixel movement velocity of each pixel point in the overlapped region in a camera coordinate system of the UAV is obtained according to the position changing information.

[0016] In some examples, for example, the change of the position information (i.e. the position changing information) of each pixel point in the overlapped region in the (N+1)th image with respect to the Nth image may be obtained by an optical flow method based on feature matching, and the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV may be obtained according to the change of the position information.

[0017] In an example of the present disclosure, block S2 may further include followings.

[0018] A moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV is calculated. In detail, in some examples, the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV may be calculated by the optical flow method based on feature matching.

[0019] In an example of the present disclosure, calculating the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV may include: calculating moving information of a same pixel point based on position information of the same pixel point in the Nth image and the (N+1)th image and obtaining a moving distance of the same pixel point in the camera coordinate system according to the moving information. As a particular example, the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV may be calculated via an equation of

where, (x1, y1) represents the position information of the pixel point in the Nth image, (x2, y2) represents the position information of the pixel point in the (N+1)th image, and (ux,uy) represents the moving distance of the pixel point in the camera coordinate system.

[0020] The block S2 may further include followings. A derivative of the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV with respect to time is found so as to obtain the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV.

[0021] In other words, for a particular example, with the optical flow method based on feature matching, a position in the (N+1)th image for each pixel point in the Nth image is matched, then the moving distance of each pixel point in the Nth image to the (N+1)th image may be calculated, and the pixel movement velocity of each pixel point in the camera coordinate system of the UAV may be obtained based on the moving distance. In detail, the optical flow method based on feature matching may include a dense algorithm and a sparse algorithm. With the dense algorithm, all pixel points in an image are participated in calculation, so as to obtain the pixel movement velocity of each pixel point in the image. While with the sparse algorithm, parts of pixel points in the image which are easy to track may be selected, and optical flow calculation is performed to the selected pixel points so as to obtain pixel movement velocities of these pixel points easy to track. In an example of the present disclosure, the practical optical flow method based on feature matching is, for example, a dense algorithm. It should be noticed that, calculating the pixel movement velocities of the pixel points in the camera coordinate system by the optical flow method based on feature matching is just an example of the present disclosure, which cannot be construed to limit the present disclosure. Other methods for calculating the pixel movement velocities of the pixel points in the camera coordinate system may also be applied in the present disclosure, which will fall in the scope of the present disclosure.

[0022] At block S3, an actual flying velocity of the UAV in a world coordinate system is obtained.

[0023] In practice, the actual flying velocity of the UAV in the world coordinate system may be measured by a velocity measurement device such as GNSS (global navigation satellite system) positioning velocity measurement (e.g. GPS (global position system), Beidou (big dipper) navigation satellite, etc.), an airspeed head, or a radar. Then the measured flying velocity of the UAV in the world coordinate system is obtained.

[0024] At block S4, a range image of each overlapped region is obtained according to the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV, the actual flying velocity of the UAV in the world coordinate system, and parameters of the airborne camera. Then the range image of each overlapped region may be integrated to obtain a range image of the preset scene. In an example of the present disclosure, the parameters of the airborne camera may include a focal length of the airborne camera.

[0025] In detail, since the airborne camera is installed on the self-stabilizing platform, it can be assumed that when the image is taken, the angular velocity of the airborne camera is always zero. In a circumstance that the angular velocity of the airborne camera is always zero or close to zero when each image is taken, the block S4 may further include followings.

[0026] Relationships are established among the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV, the actual flying velocity of the UAV in the world coordinate system, and a flying height of the UAV. In detail, for example, the relationships among the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV, the actual flying velocity of the UAV in the world coordinate system, and the flying height of the UAV may be established based on the principle of pin-hole imaging, and the relationships may be expressed as an equation of

where, vm is the actual flying velocity of the UAV in the world coordinate system, v is the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV, Z is the flying height of the UAV, and f is the focal length of the airborne camera.

[0027] The block S4 may further include followings. The equation of expressing the relationships mentioned in the block SD41 is transformed to obtain a depth value of each pixel point in the overlapped region by an equation of

where, Zi is the depth value of the ith pixel point in the overlapped region, vi is the pixel movement velocity of the ith pixel point in the camera coordinate system, vm is the actual flying velocity of the UAV in the world coordinate system, and f is the focal length of the airborne camera which is a known constant.

[0028] The block S4 may further include followings. The range image of each overlapped region is obtained according to the depth value of each pixel point in each overlapped region obtained in the block S42, and the range image of each overlapped region may be integrated to obtain the range image of the preset scene (the object to be measured).

[0029] In an example of the present disclosure, the above process may further includes determining whether an orientation of the camera coordinate system is in accordance with an orientation of the world coordinate system, and when the orientation of the camera coordinate system is not in accordance with the orientation of the world coordinate system, adjusting the orientation of the camera coordinate system to make the orientation of the camera coordinate system in accordance with the orientation of the world coordinate system.

[0030] In summary, the present disclosure calculates image depth data by combining the pixel movement velocity of each pixel point in the camera coordinate system of the UAV and the actual flying velocity of the UAV itself and obtains the range image accordingly. Thus any methods of using an image velocity (the pixel movement velocity of each pixel point in the camera coordinate system of the UAV) and the actual flying velocity of the UAV itself to obtain the range image will fall into the scope of the present disclosure.

[0031] With the method for obtaining a range image with a UAV according to embodiments of the present disclosure, the image sequence is taken by the airborne camera of the UAV. For the overlapped region of two continuous images, the pixel movement velocity of each pixel point in the camera coordinate system of the UAV is obtained based on the position changing information of each pixel point. The actual flying velocity of the UAV in the world coordinate system is measured by devices such as an airborne GPS. Then the range image may be calculated according to the relationships among the pixel movement velocities of pixel points in the camera coordinate system of the UAV, the actual flying velocity of the UAV in the world coordinate system, and the flying height of the UAV. With the method, the range image can be accurately obtained, and the process is simple and easy to achieve. Moreover, there are no requirements on energy reflection for the object to be measured, so that a measurable distance is long enough and there is no problem of energy attenuation, thereby having a wide scope of applications. Furthermore, the method may be achieved in the UAV of the related art without additional devices and therefore may benefit for reducing the load of the UAV and lower the measurement cost. And the failure in the active measurement caused by energy attenuation or absorption on the surface of the object can be avoided as well.

[0032] Embodiments of the present disclosure also provide an apparatus for obtaining a range image with a UAV.

[0033] Fig. 3 is a block diagram illustrating an apparatus for obtaining a range image with a UAV according to an embodiment of the present disclosure. As illustrated in Fig. 3, the apparatus 100 for obtaining a range image with a UAV includes a reading module 110, a calculation module 120, a measurement module 130 and an image generating module 140.

[0034] In detail, the reading module 110 is configured to read an image sequence of a predetermined scene collected by an airborne camera of a UAV, in which the Nth image and the (N+1)th image of the image sequence have an overlapping region, and a ratio of an area of the overlapping region to an area of the Nth image or a ratio of the area of the overlapping region to an area of the (N+1)th image is greater than a preset ratio. In other words, the image sequence of an object to be measured is taken by the airborne camera and two continuous images are extracted therefrom, for example, the Nth image and the (N+1)th image. Besides, the Nth image and the (N+1)th image must have the overlap region. To insure accuracy of a following optical flow calculation, the ratio of the area of the overlapping region to the area of the Nth image or the (N+1)th image needs to be greater than the preset ratio. More particularly, in an example of the present disclosure, for example, the preset ratio is 60%, that is, the area of the overlapping region accounts for more than 60% of the area of the Nth image or the (N+1)th image.

[0035] In addition, in an example of the present disclosure, to insure qualities of images taken by the airborne camera and to reduce disturbance to the following optical flow calculation that may be caused by airframe vibrations of the UAV, the airborne camera may be installed onto the UAV through a self-stabilizing platform, for example. Meanwhile, to reduce influence of distortion of the image itself taken by the airborne camera, a visual angle of the airborne camera cannot be too large. In an example of the present disclosure, the visual angle of the airborne camera is selected to be less than a preset angle. More particularly, for example, the preset angle may be 60 degree. Obviously, the preset angle is not limited to the above angle and may be selected according to requirements of an actual scene (for example, the preset angle may be less than 60 degree), and this example is just illustrated as an example.

[0036] In an example of the present disclosure, when the distortion of the image taken by the airborne camera is serious, the reading module 100 is further configured to adjust the distortion in the image sequence to make the distortion in a tolerable range for following operations.

[0037] The calculation module 120 is configured to obtain, for each pixel point in the overlapped region, position changing information of the pixel point in the (N+1)th image with respect to the Nth image and to obtain a pixel movement velocity of each pixel point in the overlapped region in a camera coordinate system of the UAV according to the position changing information. In detail, for example, the calculation module 120 is configured to obtain the change of the position information (i.e. the position changing information) of each pixel point in the overlapped region in the (N+1)th image with respect to the Nth image by an optical flow method based on feature matching, and to obtain the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV according to the change of the position information.

[0038] In an example of the present disclosure, the calculation module 120 is configured to calculate the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV via the optical flow based on feature matching. This action may further include calculating moving information of a same pixel point based on position information of the same pixel point in the Nth image and the (N+1)th image and obtaining a moving distance of the same pixel point in the camera coordinate system according to the moving information; finding a derivative of the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV with respect to time to obtain the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV.

[0039] As a particular example, the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV may be calculated via an equation of

where, (x1, y1) represents the position information of the pixel point in the Nth image, (x2, y2) represents the position information of the pixel point in the (N+1)th image, and (ux,uy) represents the moving distance of the pixel point in the camera coordinate system. With the optical flow method based on feature matching, a position in the Nth image for each pixel point in the Nth image is matched, then the moving distance of each pixel point in the Nth image to the (N+1)th image may be calculated, and the pixel movement velocity of each pixel point in the camera coordinate system of the UAV may be obtained based on the moving distance. In detail, the optical flow method based on feature matching may include a dense algorithm and a sparse algorithm. With the dense algorithm, all pixel points in an image are participated in calculation, so as to obtain the pixel movement velocity of each pixel point in the image. While with the sparse algorithm, parts of pixel points in the image which are easy to track may be selected, and optical flow calculation is performed to the selected pixel points so as to obtain pixel movement velocities of these pixel points easy to track. In an example of the present disclosure, the practical optical flow method based on feature matching may be a dense algorithm. It should be noticed that, calculating the pixel movement velocities of the pixel points in the camera coordinate system by the optical flow method based on feature matching is just an example of the present disclosure, which cannot be construed to limit the present disclosure. Other methods for calculating the pixel movement velocities of the pixel points in the camera coordinate system may also be applied in the present disclosure, which will fall in the scope of the present disclosure.

[0040] The measurement module 130 is configured to obtain an actual flying velocity of the UAV in a world coordinate system. In practice, the actual flying velocity of the UAV in the world coordinate system may be obtained by GPS, Beidou (big dipper) navigation satellite, an airspeed head or a radar.

[0041] The image generating module 140 is configured to obtain a range image of each overlapped region according to the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV, the actual flying velocity of the UAV in the world coordinate system, and parameters of the airborne camera and to obtain a range image of the preset scene through integrating the range image of each overlapped region. In an example of the present disclosure, the parameters of the airborne camera may include a focal length of the airborne camera.

[0042] In detail, since the airborne camera is installed on the self-stabilizing platform, it can be assumed that when the image is taken, the angular velocity of the airborne camera is always zero. In an example of the present disclosure, the image generating module 140 is configured to establish relationships among the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV, the actual flying velocity of the UAV in the world coordinate system, and a flying height of the UAV. In detail, the image generating module 140 may be configured to establish the relationships among the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV, the actual flying velocity of the UAV in the world coordinate system, and a flying height of the UAV based on the principle of pin-hole imaging. The relationships may be expressed as an equation of:

where, vm is the actual flying velocity of the UAV in the world coordinate system, v is the pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV, Z is the flying height of the UAV, and f is the focal length of the airborne camera.

[0043] Then a depth value of each pixel point in the overlapped region is obtained based on the above relationships as follows:

where, Zi is the depth value of the ith pixel point in the overlapped region, vi is the pixel movement velocity of the ith pixel point in the camera coordinate system, vm is the actual flying velocity of the UAV in the world coordinate system, and f is the focal length of the airborne camera which is a known constant.

[0044] At last, the range image of each overlapped region is obtained according to the depth value of each pixel point in each overlapped region, and the range image of each overlapped region may be integrated to obtain the range image of the preset scene (the object to be measured).

[0045] In an example of the present disclosure, the apparatus 100 for obtaining a range image with a UAV further includes, for example, an adjusting module (not illustrated in the figures). The adjusting module is configured to determine whether an orientation of the camera coordinate system is in accordance with an orientation of the world coordinate system, and to adjust the orientation of the camera coordinate system to make the orientation of the camera coordinate system in accordance with the orientation of the world coordinate system when the orientation of the camera coordinate system is not in accordance with the orientation of the world coordinate system.

[0046] In summary, the present disclosure calculates image depth data by combining the pixel movement velocity of each pixel point in the camera coordinate system of the UAV and the actual flying velocity of the UAV itself and obtains the range image accordingly. Thus any methods of using an image velocity (the pixel movement velocity of each pixel point in the camera coordinate system of the UAV) and the actual flying velocity of the UAV itself to obtain the range image will fall into the scope of the present disclosure.

[0047] With the apparatus for obtaining a range image with a UAV according to embodiments of the present disclosure, the image sequence captured by the airborne camera of the UAV is read by the reading module. For the overlapped region of two continuous images, the pixel movement velocity of each pixel point in the camera coordinate system of the UAV is obtained based on the position changing information of each pixel point by the calculation module. The actual flying velocity of the UAV in the world coordinate system is measured by the measurement module, for example devices such as an airborne GPS. Then the range image may be calculated according to the relationships among the pixel movement velocities of pixel points in the camera coordinate system of the UAV, the actual flying velocity of the UAV in the world coordinate system, and the flying height of the UAV by the image generating module. With the apparatus, the range image can be accurately obtained. Moreover, there are no requirements on energy reflection for the object to be measured, so that a measurable distance is long enough and there is no problem of energy attenuation, thereby having a wide scope of applications. Furthermore, the apparatus may be achieved in the UAV of the related art without additional devices and therefore may benefit for reducing the load of the UAV and lower the measurement cost. And the failure in the active measurement caused by energy attenuation or absorption on the surface of the object can be avoided as well.

[0048] Embodiments of the present disclosure also provide a UAV. The UAV includes an airborne camera, a velocity measurement device, a processor, and an airframe. The airborne camera and the velocity measurement device are coupled to the processor respectively. The airframe is configured for the airborne camera, the velocity measurement device and the processor to be installed onto. The airborne camera is configured to collect an image sequence of a preset scene. The velocity measurement device is configured to measure or calculate an actual flying velocity of the UAV in the world coordinate system. In practice, the velocity measurement device may include a GNSS (global navigation satellite system) positioning velocity measurement (e.g. GPS (global position system), Beidou (big dipper) navigation satellite, etc.), an airspeed head or a radar.

[0049] The processor is configured to perform the above method for obtaining a range image with a UAV. In other words, the processor includes the apparatus for obtaining a range image with a UAV described in above embodiments of the present disclosure.

[0050] In an example of the present disclosure, the UAV further includes a self-stabilizing platform, and the airborne camera may be installed onto the airframe through the self-stabilizing platform.

[0051] With the UAV according to embodiments of the present disclosure, the airborne camera, the velocity measurement device and the processor are installed on the airframe. The image sequence is taken by the airborne camera and read by the processor. For the overlapped region of two continuous images, the pixel movement velocity of each pixel point in the camera coordinate system of the UAV is obtained based on the position changing information of each pixel point. The actual flying velocity of the UAV in the world coordinate system is measured by a device such as an airborne GPS. Then the range image may be calculated according to the relationships among the pixel movement velocities of pixel points in the camera coordinate system of the UAV, the actual flying velocity of the UAV in the world coordinate system, and the flying height of the UAV. Therefore, the range image can be accurately obtained. Moreover, there are no requirements on energy reflection for the object to be measured, so that a measurable distance is long enough and there is no problem of energy attenuation, thereby having a wide scope of applications. Furthermore, the method may be achieved in the UAV of the related art without additional devices and therefore may benefit for reducing the load of the UAV and lower the measurement cost. And the failure in the active measurement caused by energy attenuation or absorption on the surface of the object can be avoided as well.

[0052] The serial numbers of embodiments in the present disclosure are just for description and do not imply that the corresponding embodiment is preferable or advantageous.

[0053] In above embodiments of the present disclosure, particular emphasis may be put on different parts, and details of parts that are not described in some embodiments may be found in other embodiments.

[0054] It should be understood that, the technical contents disclosed in the embodiments of the present disclosure can also be achieved in other manners. The above-described apparatus embodiments are merely for the purpose of illustration. For example, the partition of modules may be logical and functional, and can be achieved in different ways of partition. For example, a plurality of modules of assemblies can be combined or integrated into another system, or some features may be neglected or not be executed. In addition, the illustrated or discussed terms "coupled", "directly coupled", or "communication connection" there-between may be indirectly coupled or communication connection through some interfaces, units or modules, and can be electrically or in other forms.

[0055] Those units described as separated components or modules may be or may not be physically separated; those units described as a display component may be or may not be a physical unit, i.e., either located at one place or distributed onto a plurality of network units. The object of the present disclosure may be achieved by part or all of modules in accordance with practical requirements.

[0056] In addition, individual functional units in the embodiments of the present disclosure may be integrated in one processing module or may be separately physically present, or two or more units may be integrated in one module. The integrated module as described above may be achieved in the form of hardware, or may be achieved in the form of a software functional module.

[0057] When the integrated module is achieved in the form of a software functional module and sold or used as a separate product, the integrated module may also be stored in a computer readable storage medium. Based on this understanding, the substance of technical solutions of the present disclosure or in other words the parts which contributes to the prior art or all or part of the solution may be achieved or expressed in a software product. The software product may be stored in a computer-readable storage medium which includes instructions for a computer device (personal computer, server or network device) to perform all or part of the steps in the methods described in embodiments of the present disclosure. The computer readable storage medium may include a flash disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disc, a magnetic disc, an optical disc, or any medium that can store program codes.

[0058] Although explanatory embodiments have been shown and described, it would be appreciated by those skilled in the art that changes, alternatives, and modifications can be made in the embodiments.


Claims

1. A method for obtaining a range image with an unmanned aerial vehicle UAV, comprising:

reading (S1) an image sequence of a predetermined scene collected by an airborne camera of the UAV, wherein the Nth image and the (N+1)th image of the image sequence have an overlapping region, and a ratio of an area of the overlapping region to an area of the Nth image or a ratio of the area of the overlapping region to an area of the (N+1)th image is greater than a preset ratio;

for each pixel point in the overlapped region, calculating (S2) a moving distance of each pixel point in the overlapped region in a camera coordinate system of the UAV; and finding (S2) a derivative of the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV with respect to time to obtain a pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV;

obtaining (S3) an actual flying velocity of the UAV in a world coordinate system by a velocity measurement device;

being characterized in that, the method further comprising:
obtaining a depth value of the ith pixel point (Zi) according to a ratio between the actual flying velocity (vm) of the UAV in the world coordinate system and the pixel movement velocity (vi) of each pixel point in the overlapped region in the camera coordinate system of the UAV, and the focal length (f) of the airborne camera, obtaining a range image of each overlapped region according to the depth value of the ith pixel point (Zi), and obtaining a range image of the preset scene through integrating the range image of each overlapped region (S4).


 
2. The method according to claim 1, wherein,:
the depth value of the ith pixel point (Zi) is obtained by a formula of:


 
3. The method according to claim 2, further comprising:

determining whether an orientation of the camera coordinate system is in accordance with an orientation of the world coordinate system;

when the orientation of the camera coordinate system is not in accordance with the orientation of the world coordinate system, adjusting the orientation of the camera coordinate system so as to make the orientation of the camera coordinate system in accordance with the orientation of the world coordinate system.


 
4. The method according to any one of claims 1-3, wherein, a visual angle of the airborne camera is less than a preset angle, and the preset angle is equal to or less than 60 degree.
 
5. The method according to any one of claims 1-4, wherein, before calculating the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV, further comprising: adjusting distortion of images in the image sequence.
 
6. An apparatus for obtaining a range image with an unmanned aerial vehicle UAV, comprising:

a reading module (110), configured to read an image sequence of a predetermined scene collected by an airborne camera of the UAV, wherein the Nth image and the (N+1)th image of the image sequence have an overlapping region, and a ratio of an area of the overlapping region to an area of the Nth image or a ratio of the area of the overlapping region to an area of the (N+1)th image is greater than a preset ratio;

a calculation module (120), configured to calculate, for each pixel point in the overlapped region, a moving distance of each pixel point in the overlapped region in a camera coordinate system of the UAV; and find a derivative of the moving distance of each pixel point in the overlapped region in the camera coordinate system of the UAV with respect to time to obtain a pixel movement velocity of each pixel point in the overlapped region in the camera coordinate system of the UAV;

a measurement module (130), configured to obtain an actual flying velocity of the UAV in a world coordinate system by a velocity measurement device;

being characterized in that, the device further comprises:
an image generating module (140), configured to obtain a depth value of the ith pixel point (Zi) according to a ratio between the actual flying velocity (vm) of the UAV in the world coordinate system and the pixel movement velocity (vi) of each pixel point in the overlapped region in the camera coordinate system of the UAV, and the focal length (f) of the airborne camera, obtain a range image of each overlapped region according to the depth value of the ith pixel point (Zi), and to obtain a range image of the preset scene through integrating the range image of each overlapped region.


 
7. The apparatus according to claim 6, wherein,
the depth value of the ith pixel point (Zi) is obtained by a formula of:


 
8. The apparatus according to claim 7, further comprising:
an adjusting module, configured to determine whether an orientation of the camera coordinate system is in accordance with an orientation of the world coordinate system, and to adjust the orientation of the camera coordinate system to make the orientation of the camera coordinate system in accordance with the orientation of the world coordinate system when the orientation of the camera coordinate system is not in accordance with the orientation of the world coordinate system.
 
9. The apparatus according to any one of claims 6-8, wherein, a visual angle of the airborne camera is less than a preset angle, and the preset angle is equal to or less than 60 degree.
 
10. The apparatus according to any one of claims 6-9, wherein, the airborne camera is further configured to adjust distortion of images in the image sequence.
 


Ansprüche

1. Verfahren zum Erhalten eines Bereichsbilds mit einem unbemannten Luftfahrzeug UAV, das Folgendes umfasst:

Lesen (S1) einer Bildabfolge einer vorbestimmten Szene, die von einer Luftbildkamera des UAV gesammelt wird, wobei das N-te Bild und das (N+1)-te Bild der Bildabfolge einen überlappenden Bereich aufweisen, und ein Verhältnis einer Fläche des überlappenden Bereichs zu einer Fläche des N-ten Bilds oder ein Verhältnis der Fläche des überlappenden Bereichs zu einer Fläche des (N+1)-ten Bilds größer ist als ein voreingestelltes Verhältnis;

für jeden Pixelpunkt in dem überlappten Bereich Berechnen (S2) einer Bewegungsentfernung jedes Pixelpunkts in dem überlappten Bereich in einem Kamerakoordinatensystem des UAV; und Finden (S2) einer Ableitung der Bewegungsentfernung jedes Pixelpunkts in dem überlappten Bereich in dem Kamerakoordinatensystem des UAV in Bezug auf Zeit, um eine Pixelbewegungsgeschwindigkeit jedes Pixelpunkts in dem überlappten Bereich in dem Kamerakoordinatensystem des UAV zu erhalten;

Erhalten (S3) einer tatsächlichen Fluggeschwindigkeit des UAV in einem Weltkoordinatensystem durch eine Geschwindigkeitsmessvorrichtung;

dadurch gekennzeichnet, dass das Verfahren ferner Folgendes umfasst:
Erhalten eines Tiefenwerts des i-ten Pixelpunkts (Zi) gemäß einem Verhältnis zwischen der tatsächlichen Fluggeschwindigkeit (vm) des UAV in dem Weltkoordinatensystem und der Pixelbewegungsgeschwindigkeit (vi) jedes Pixelpunkts in dem überlappten Bereich in dem Kamerakoordinatensystem des UAV, und der Brennweite (f) der Luftbildkamera, Erhalten eines Bereichsbilds jedes überlappten Bereichs gemäß dem Tiefenwert des i-ten Pixelpunkts (Zi), und Erhalten eines Bereichsbilds der voreingestellten Szene durch Integrieren des Bereichsbilds jedes überlappten Bereichs (S4).


 
2. Verfahren nach Anspruch 1, wobei:
der Tiefenwert des i-ten Pixelpunkts (Zi) durch folgende Formel erhalten wird:


 
3. Verfahren nach Anspruch 2, das ferner Folgendes umfasst:

Bestimmen, ob eine Ausrichtung des Kamerakoordinatensystems mit einer Ausrichtung des Weltkoordinatensystems übereinstimmt;

wenn die Ausrichtung des Kamerakoordinatensystems nicht mit der Ausrichtung des Weltkoordinatensystems übereinstimmt, Einstellen der Ausrichtung des Kamerakoordinatensystems derart, dass die Ausrichtung des Kamerakoordinatensystems mit der Ausrichtung des Weltkoordinatensystems übereinstimmt.


 
4. Verfahren nach einem der Ansprüche 1 bis 3, wobei ein Blickwinkel der Luftbildkamera kleiner ist als ein voreingestellter Winkel, und der voreingestellte Winkel gleich oder kleiner ist als 60 Grad.
 
5. Verfahren nach einem der Ansprüche 1 bis 4, das vor dem Berechnen der Bewegungsentfernung jedes Pixelpunkts in dem überlappten Bereich in dem Kamerakoordinatensystems des UAV ferner Folgendes umfasst: Einstellen einer Verzerrung von Bildern in der Bildabfolge.
 
6. Gerät zum Erhalten eines Bereichsbilds mit einem unbemannten Luftfahrzeug UAV, das Folgendes umfasst:

ein Lesemodul (110), das konfiguriert ist, um eine Bildabfolge einer vorbestimmten Szene zu lesen, die von einer Luftbildkamera des UAV gesammelt wird, wobei das N-te Bild und das (N + 1)-te Bild der Bildabfolge einen überlappenden Bereich aufweisen, und ein Verhältnis einer Fläche des überlappenden Bereichs zu einer Fläche des N-ten Bilds oder ein Verhältnis der Fläche des überlappenden Bereichs zu einer Fläche des (N+1)-ten Bilds größer ist als ein voreingestelltes Verhältnis;

eine Rechenmodul (120), das konfiguriert ist, um für jeden Pixelpunkt in dem überlappten Bereich eine Bewegungsentfernung jedes Pixelpunkts in dem überlappten Bereich in einem Kamerakoordinatensystem des UAV zu berechnen; und eine Ableitung der Bewegungsentfernung jedes Pixelpunkts in dem überlappten Bereich in dem Kamerakoordinatensystems des UAV in Bezug auf Zeit zu finden, um eine Pixelbewegungsgeschwindigkeit jedes Pixelpunkts in dem überlappten Bereich in dem Kamerakoordinatensystems des UAV zu erhalten;

ein Messmodul (130), das konfiguriert ist, um eine tatsächliche Fluggeschwindigkeit des UAV in einem Weltkoordinatensystem durch eine Geschwindigkeitsmessvorrichtung zu erhalten;

dadurch gekennzeichnet, dass die Vorrichtung ferner Folgendes umfasst:
ein Bilderzeugungsmodul (140), das konfiguriert ist, um einen Tiefenwert des i-ten Pixelpunkts (Zi) gemäß einem Verhältnis zwischen der tatsächlichen Fluggeschwindigkeit (vm) des UAV in dem Weltkoordinatensystem und der Pixelbewegungsgeschwindigkeit (vi) jedes Pixelpunkts in dem überlappten Bereich in dem Kamerakoordinatensystems des UAV und die Brennweite (f) der Luftbildkamera zu erhalten, ein Bereichsbild jedes überlappten Bereichs gemäß dem Tiefenwert des i-ten Pixelpunkts (Zi) zu erhalten, und ein Bereichsbild der voreingestellten Szene durch Integrieren des Bereichsbilds jedes überlappten Bereichs zu erhalten.


 
7. Gerät nach Anspruch 6, wobei
der Tiefenwert des i-ten Pixelpunkts (Zi) durch die folgende Formel erhalten wird:


 
8. Gerät nach Anspruch 7, das ferner Folgendes umfasst:
ein Einstellmodul, das konfiguriert ist, um zu bestimmen, ob eine Ausrichtung des Kamerakoordinatensystems mit einer Ausrichtung des Weltkoordinatensystems übereinstimmt, und die Ausrichtung des Kamerakoordinatensystems derart einzustellen, dass sie mit der Ausrichtung des Weltkoordinatensystems übereinstimmt, wenn die Ausrichtung des Kamerakoordinatensystems nicht mit der Ausrichtung des Weltkoordinatensystems übereinstimmt.
 
9. Gerät nach einem der Ansprüche 6 bis 8, wobei ein Blickwinkel der Luftbildkamera kleiner ist als ein voreingestellter Winkel, und der voreingestellte Winkel gleich oder kleiner ist als 60 Grad.
 
10. Gerät nach einem der Ansprüche 6 bis 9, wobei die Luftbildkamera ferner konfiguriert ist, um Verzerrung von Bildern in der Bildabfolge einzustellen.
 


Revendications

1. Procédé pour obtenir une image de distance avec un véhicule aérien sans pilote, comprenant de :

lire (S1) une séquence d'images d'une scène prédéterminée collectée par une caméra aéroportée de l'UAV, dans laquelle la Nième image et la (N + 1)ème image de la séquence d'images ont une région de chevauchement et un rapport d'une zone de la région de chevauchement sur une zone de la Nième image ou un rapport de la zone de la région de chevauchement sur une zone de la (N + 1)ème image est supérieure à un rapport prédéfini ;

pour chaque point de pixel dans la région de chevauchement, calculer (S2) une distance de déplacement de chaque point de pixel dans la région de chevauchement dans un système de coordonnées de caméra de l'UAV ; et trouver (S2) une dérivée de la distance de déplacement de chaque point de pixel dans la région de chevauchement dans le système de coordonnées de caméra de l'UAV par rapport au temps pour obtenir une vitesse de déplacement de pixel de chaque point de pixel dans la région de chevauchement dans le système de coordonnées de caméra de l'UAV ;

obtenir (S3) une vitesse de vol réelle de l'UAV dans un système de coordonnées mondial par un dispositif de mesure de vitesse ;

caractérisé en ce que le procédé comprend en outre de :
obtenir une valeur de profondeur du ième point de pixel (Zi) en fonction d'un rapport entre la vitesse de vol réelle (vm) de l'UAV dans le système de coordonnées mondial et la vitesse de déplacement de pixel (vi) de chaque point de pixel dans la région chevauchée dans la système de coordonnées de la caméra de l'UAV et la distance focale (f) de la caméra aéroportée, obtenir une image de distance de chaque région chevauchée en fonction de la valeur de profondeur du ième point pixel (Zi) et obtenir une image de distance de la scène prédéfinie en intégrant l'image de distance de chaque région chevauchée (S4).


 
2. Procédé selon la revendication 1, dans lequel :
la valeur de profondeur du ième point pixel (Zi) est obtenue par une formule de :


 
3. Procédé selon la revendication 2, comprenant en outre de :

déterminer si une orientation du système de coordonnées de caméra est conforme à une orientation du système de coordonnées mondial ;

lorsque l'orientation du système de coordonnées de la caméra n'est pas conforme à l'orientation du système de coordonnées mondial, régler l'orientation du système de coordonnées de la caméra de manière à rendre l'orientation du système de coordonnées de la caméra conforme à l'orientation du système de coordonnées mondial.


 
4. Procédé selon une quelconque des revendications 1 à 3, dans lequel, un angle visuel de la caméra aéroportée est inférieur à un angle prédéfini, et l'angle prédéfini est égal ou inférieur à 60 degrés.
 
5. Procédé selon une quelconque des revendications 1 à 4, dans lequel, avant de calculer la distance de déplacement de chaque point de pixel dans la région chevauchée dans le système de coordonnées de caméra de l'UAV, comprenant en outre : l'ajustement de la distorsion des images dans la séquence d'images.
 
6. Appareil pour obtenir une image de distance avec un véhicule aérien sans pilote, comprenant :

un module de lecture (110), configuré pour lire une séquence d'images d'une scène prédéterminée collectée par une caméra aéroportée de l'UAV, dans lequel la Nième image et la (N + 1)ème image de la séquence d'images ont une région de chevauchement, et un rapport d'une zone de la région de chevauchement sur une zone de la Nième image ou un rapport de la zone de la région de chevauchement sur une zone de la (N + 1)ème image est supérieur à un rapport prédéfini ;

un module de calcul (120), configuré pour calculer, pour chaque point de pixel dans la région de chevauchement, une distance de déplacement de chaque point de pixel dans la région de chevauchement dans un système de coordonnées de caméra de l'UAV ; et trouver une dérivée de la distance de déplacement de chaque point de pixel dans la région chevauchée dans le système de coordonnées de caméra de l'UAV par rapport au temps pour obtenir une vitesse de déplacement de pixel de chaque point de pixel dans la région chevauchée dans le système de coordonnées de caméra de l'UAV ;

un module de mesure (130), configuré pour obtenir une vitesse de vol réelle de l'UAV dans un système de coordonnées mondial par un dispositif de mesure de vitesse ;

caractérisé en ce que le dispositif comprend en outre :
un module de génération d'image (140), configuré pour obtenir une valeur de profondeur du ième point de pixel (Zi) selon un rapport entre la vitesse de vol réelle (vm) de l'UAV dans le système de coordonnées mondial et la vitesse de déplacement des pixels (vi) de chaque point de pixel dans la région chevauchée dans le système de coordonnées de la caméra de l'UAV, et la distance focale (f) de la caméra aéroportée, obtenir une image de distance de chaque région chevauchée en fonction de la valeur de profondeur du ième point de pixel (Zi), et obtenir une image de distance de la scène prédéfinie en intégrant l'image de distance de chaque région chevauchée.


 
7. Appareil selon la revendication 6, dans lequel
la valeur de profondeur du ième point pixel (Zi) est obtenue par une formule de :


 
8. Appareil selon la revendication 7, comprenant en outre :
un module de réglage, configuré pour déterminer si une orientation du système de coordonnées de caméra est conforme à une orientation du système de coordonnées mondial, et pour ajuster l'orientation du système de coordonnées de caméra pour faire l'orientation du système de coordonnées de caméra conformément à l'orientation du système de coordonnées mondial lorsque l'orientation du système de coordonnées de la caméra n'est pas conforme à l'orientation du système de coordonnées mondial.
 
9. Appareil selon une quelconque des revendications 6 à 8, dans lequel, un angle visuel de la caméra aéroportée est inférieur à un angle prédéfini, et l'angle prédéfini est égal ou inférieur à 60 degrés.
 
10. Appareil selon une quelconque des revendications 6 à 9, dans lequel la caméra aéroportée est en outre configurée pour ajuster la distorsion des images dans la séquence d'images.
 




Drawing











Cited references

REFERENCES CITED IN THE DESCRIPTION



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Non-patent literature cited in the description