Unmanned equipment video transmission method, system and equipment based on cloud platform

Abstract

The present invention relates to the field of video transmission technology, and specifically to a method, system and device for video transmission of unmanned equipment based on a cloud platform. The present invention obtains the Euler angle of the change of the motion posture of the unmanned equipment according to the acceleration data; obtains the matching direction between image frames in the video data according to the yaw Euler angle; analyzes the offset vector of the image frame in the video data according to the roll Euler angle and the pitch Euler angle, and obtains the corrected matching direction between the image frames in the video data in combination with the matching direction; matches the image frames in the video data according to the corrected matching direction, completes the video compression and upload to the cloud platform. The present invention adjusts the image macroblock search strategy of the inter-frame compression in the video compression process in combination with the dynamic characteristics of the unmanned equipment during operation, so that the search of the image macroblock is more accurate and faster, and the speed and effect of the inter-frame compression are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of video transmission, and in particular to a method, system and device for transmitting video of unmanned equipment based on a cloud platform. Background Art

[0002] With the rapid development of unmanned equipment technology, its application in many fields such as aerial photography, monitoring, logistics, and agriculture is becoming more and more extensive. The high-definition cameras carried by unmanned equipment can capture high-quality video streams and provide rich visual data for various applications. However, when unmanned equipment is performing tasks, it is limited by battery capacity and wireless transmission bandwidth. How to efficiently transmit high-quality video data has become a technical challenge.

[0003] In the existing unmanned equipment video transmission system, video compression technology is a key link. Although traditional video compression standards, such as H.264 / AVC and H.265 / HEVC, can effectively reduce the size of video data, they need to search for similar macroblocks in the reference image frame when performing inter-frame compression. This search process often uses one or more search strategies to find similar macroblocks and achieve inter-frame compression.

[0004] When unmanned devices are operating in the air, they usually adjust their attitude, which gradually adjusts their forward direction (the direction of the nose) to align with the forward direction. When the unmanned device is operating stably, the inter-frame compression of video data only needs to search in a specific direction to obtain the best results; however, when the unmanned device is turning, since the unmanned device cannot adjust its own direction instantly, the forward direction of the fuselage deviates from the actual direction of movement. The effect of using a search strategy in a specific direction in the video resources collected by the unmanned device will be greatly reduced, thereby extending the search time and compression efficiency of inter-frame compression. Summary of the invention

[0005] In order to solve the above technical problems, the purpose of the present invention is to provide a method, system and device for unmanned equipment video transmission based on a cloud platform.

[0006] According to a first aspect of an embodiment of the present invention, a method for transmitting video of an unmanned device based on a cloud platform is provided, and the technical solution adopted is specifically as follows:

[0007] Obtain video data collected by unmanned equipment and obtain acceleration data of unmanned equipment;

[0008] According to the acceleration data, the Euler angles of the motion posture change of the unmanned equipment are obtained, and the Euler angles include yaw Euler angle, roll Euler angle, and pitch Euler angle;

[0009] According to the yaw Euler angle, obtaining a matching direction between image frames in the video data;

[0010] Analyzing the offset vector of the image frame in the video data according to the rolling Euler angle and the pitching Euler angle, and obtaining the corrected matching direction between the image frames in the video data in combination with the matching direction;

[0011] According to the corrected matching direction, the image frames in the video data are matched to complete the video compression and upload to the cloud platform.

[0012] In some embodiments of the present invention, after collecting the video data acquired by the unmanned equipment, the method further includes:

[0013] Dividing the video data into GOP groups to obtain GOP structure frame groups;

[0014] Get the update frequency of the unmanned equipment flight control system;

[0015] In the GOP structure frame group, the P frames are divided in combination with the update frequency, and each B frame is inter-frame compressed with the previous P frame.

[0016] In some embodiments of the present invention, analyzing the offset vector of the image frame in the video data according to the rolling Euler angle and the pitching Euler angle, and obtaining the corrected matching direction between the image frames in the video data in combination with the matching direction, includes:

[0017] Obtaining shooting parameters, shooting height and flight speed of the unmanned equipment;

[0018] According to the pitch Euler angle, in combination with the shooting parameters and the shooting height, analyzing the offset vector of the image frame in the video data caused by the pitch Euler angle to obtain a pitch offset vector;

[0019] According to the rolling Euler angle and the pitching Euler angle, in combination with the shooting parameters and the shooting height, analyzing the offset vector of the image frame in the video data caused by the rolling Euler angle to obtain a rolling offset vector;

[0020] Obtaining a yaw vector according to the matching direction, in combination with the flight speed and the update frequency;

[0021] The pitch offset vector, the roll offset vector and the yaw vector are combined to obtain a correction matching direction between image frames in the video data.

[0022] In some embodiments of the present invention, analyzing the offset vector of the image frame in the video data caused by the pitch Euler angle in combination with the shooting parameters and the shooting height to obtain the pitch offset vector includes:

[0023] According to the pitch Euler angle and in combination with the shooting height, an actual change distance of the center point of the image frame in the video data is obtained;

[0024] According to the actual change distance, in combination with the shooting parameters and the shooting height, the pixel change distance of the center point is obtained;

[0025] Obtaining a projection unit vector of the pitch Euler angle in the image frame;

[0026] A pitch offset vector is obtained according to the pixel change distance and the projection unit vector of the pitch Euler angle.

[0027] In some embodiments of the present invention, according to the rolling Euler angle and the pitching Euler angle, in combination with the shooting parameters and the shooting height, analyzing the offset vector of the image frame in the video data caused by the rolling Euler angle to obtain the rolling offset vector includes:

[0028] According to the pitch Euler angle and in combination with the shooting height, an actual change distance of the center point of the image frame in the video data is obtained;

[0029] According to the actual change distance, in combination with the shooting parameters and the shooting height, the pixel change distance of the center point is obtained;

[0030] Obtaining a projection unit vector of the rolling Euler angle in the image frame;

[0031] A rolling offset vector is obtained according to the pixel change distance and the projection unit vector of the rolling Euler angle.

[0032] In some embodiments of the present invention, combining the pitch offset vector, the roll offset vector and the yaw vector to obtain a correction matching direction between image frames in the video data includes:

[0033] combining the pitch offset vector, the roll offset vector and the yaw vector to obtain a total offset vector;

[0034] Preset matching angle sequence;

[0035] The closest angle of the total offset vector is determined in the preset matching angle sequence, and the closest angle is used as the correction matching direction between image frames in the video data.

[0036] In some embodiments of the present invention, the shooting parameters include: the focal length of a camera lens, the width of a camera lens, and the width of an image frame in the collected video data.

[0037] In some embodiments of the present invention, matching the image frames in the video data according to the corrected matching direction, completing video compression and uploading to the cloud platform, includes:

[0038] Dividing the video data into macroblocks;

[0039] According to the corrected matching direction, performing macroblock matching on the image frames in the video data;

[0040] The video data after macroblock matching is compressed using an H264 compression algorithm;

[0041] The compressed video data is uploaded to the cloud platform.

[0042] According to a second aspect of an embodiment of the present invention, a cloud platform-based unmanned equipment video transmission system is provided, comprising:

[0043] A data acquisition module is used to collect video data acquired by unmanned equipment and to collect acceleration data of unmanned equipment;

[0044] An Euler angle acquisition module is used to obtain the Euler angle of the motion posture change of the unmanned equipment according to the acceleration data, and the Euler angle includes the yaw Euler angle, the roll Euler angle, and the pitch Euler angle;

[0045] a matching direction analysis module, configured to obtain a matching direction between image frames in the video data according to the yaw Euler angle; and to analyze an offset vector of an image frame in the video data according to the roll Euler angle and the pitch Euler angle, and obtain a corrected matching direction between image frames in the video data in combination with the matching direction;

[0046] The video compression module is used to match the image frames in the video data according to the correction matching direction, complete the video compression and upload it to the cloud platform.

[0047] According to a third aspect of an embodiment of the present invention, a cloud platform-based unmanned device video transmission device is provided, comprising:

[0048] A memory and a processor, wherein:

[0049] The memory is used to store program code;

[0050] The processor is used to read the program code stored in the memory and execute the method described in the first aspect of the embodiment of the present invention.

[0051] Compared with the prior art, the unmanned equipment video transmission method, system and device based on the cloud platform provided by the present invention have the following beneficial effects:

[0052] The present invention obtains the matching direction between image frames in the video data by analyzing the yaw Euler angle; then analyzes the offset vector of the image frame in the video data according to the roll Euler angle and the pitch Euler angle, and obtains the correction matching direction between image frames in the video data in combination with the matching direction; matches the image frames in the video data according to the correction matching direction, and completes video compression and uploading to the cloud platform. That is, the present invention adjusts the image macroblock search strategy of inter-frame compression in the video compression process in combination with the dynamic characteristics of the unmanned equipment during operation, thereby making the search of image macroblocks more accurate and rapid, and improving the speed and effect of inter-frame compression; at the same time, the present invention efficiently transmits the compressed video data to the cloud platform, realizes cloud-based processing and distribution of video data, and meets the requirements of real-time and high efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 A basic flow chart of a cloud platform-based unmanned equipment video transmission method provided by an embodiment of the present invention;

[0055] Figure 2 A top view of an unmanned device provided by an embodiment of the present invention;

[0056] Figure 3 A schematic diagram of a change from an original coordinate system xyz to a new coordinate system XYZ provided by an embodiment of the present invention;

[0057] Figure 4 A schematic diagram of a basic flow chart of a method for obtaining a correction matching direction provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the cloud platform-based unmanned equipment video transmission method, system and equipment proposed by the present invention, its specific implementation method, structure, features and effects in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. Terms such as "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of further restrictions, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the article or device including the element.

[0060] The following is a detailed description of a specific solution of a cloud platform-based unmanned equipment video transmission method provided by the present invention in conjunction with the accompanying drawings.

[0061] See also Figure 1 , which shows the basic process of a cloud platform-based unmanned equipment video transmission method provided by an embodiment of the present invention.

[0062] like Figure 1 As shown, an unmanned device video transmission method based on a cloud platform provided by an embodiment of the present invention specifically includes:

[0063] S100: Acquire video data collected by the unmanned equipment, and acquire acceleration data of the unmanned equipment.

[0064] First, obtain the video data collected by the high-definition camera on the unmanned device, where the video data contains several image frames. Install angular accelerometers in three different directions on the unmanned device. The three angular accelerometers are installed in the three directions of xyz (such as Figure 2 Or install a 3-axis accelerometer on the unmanned device to collect the acceleration in the xyz directions at different times on the unmanned device. , where the positive directions of acceleration are Figure 2 Mark the direction.

[0065] In some embodiments of the present invention, after collecting the video data obtained by the unmanned equipment, it also includes: dividing the video data into GOP groups with a length of 10-15 frames to obtain several GOP structure frame groups. At the same time, the update frequency of the flight control system of the unmanned equipment is obtained. In the GOP structure frame group, the P frame is divided in combination with the update frequency of the flight control system of the unmanned equipment; specifically, in the GOP structure frame group, the I frame is used as the starting point, and the P frame is evenly inserted according to the update frequency of the flight control system of the unmanned equipment; taking a 60-frame video as an example, the interval between adjacent image frames is 16.7ms. If the update frequency of the flight control system of the unmanned equipment is 30ms, then in the GOP structure frame group, the P frame is inserted at intervals of 1 frame to better perform motion prediction; then in the GOP structure frame group, each B frame is inter-frame compressed with the previous P frame.

[0066] At this point, the acquisition and processing of the video data acquired by the unmanned equipment and the acquisition of the acceleration data of the unmanned equipment have been completed.

[0067] S200: Obtaining the Euler angles of the motion posture change of the unmanned equipment according to the acceleration data, where the Euler angles include the yaw Euler angle, the roll Euler angle, and the pitch Euler angle.

[0068] During the flight of unmanned equipment, attitude angle is a way to describe the motion attitude, just like a compass and a map can help us determine the direction. The most common representation method is the Euler angle. The Euler angle consists of three independent angles, generally represented by Yaw, Pitch, and Roll.

[0069] In some embodiments of the present invention, the Euler angles of the motion posture change of the unmanned equipment are obtained based on the acceleration data, and the Euler angles include the yaw Euler angle, the roll Euler angle, and the pitch Euler angle.

[0070] Specifically, the Euler angle calculation method is:

[0071] like Figure 3 As shown in the figure, when the motion posture of the unmanned equipment changes, it can be understood as the change of two coordinate systems, that is, from the original coordinate system xyz to the new coordinate system XYZ. Figure 3 The N axis in represents the intersection line, which is the line intersecting the xy plane of the original coordinate system and the XY plane of the new coordinate system.

[0072] Get the Euler angles of the original coordinate system xyz and the new coordinate system XYZ .in, Indicates the angle between the x-axis and the N-axis of the original coordinate system; Indicates the angle between the z-axis of the original coordinate system and the z-axis of the new coordinate system; Represents the angle between the N axis and the X axis of the new coordinate system. It can also be understood as It is the rotation around the z-axis of the original coordinate system, indicating the yaw of the unmanned equipment; It is around The rotation of the axis indicates the rolling of the unmanned equipment; It is around The rotation of the axis represents the pitch of the unmanned equipment. represents the x-axis after one rotation, Represents the z-axis after secondary rotation.

[0073] At this time, calculate the Euler angles:

[0074]

[0075]

[0076]

[0077] in, ;

[0078] In the formula, The yaw Euler angle that indicates the change in the motion posture of the unmanned equipment; The rolling Euler angle that represents the change in the motion posture of the unmanned equipment; The pitch Euler angle that indicates the change in the motion posture of the unmanned equipment; Indicates the acceleration of the unmanned equipment in the y direction, The value range of is (-1, 1); Indicates the acceleration of the unmanned equipment in the z direction.

[0079] It should be noted that The value range of is (-1, 1), where negative values ​​indicate deceleration. The flight control system will limit the maneuvering of the drone to ensure that the acceleration vector does not exceed the range, thereby ensuring the safety of the flight and the stability of the control system. In addition, other methods can also be used to calculate the Euler angle. The calculation of the Euler angle is a prior art and will not be repeated here.

[0080] At this point, the calculation of the Euler angles of the unmanned equipment's motion posture changes has been completed.

[0081] When the unmanned equipment is running smoothly, the speed of the unmanned equipment is relatively stable, and the head of the unmanned equipment is consistent with the actual running direction. The image frames in the collected video data mainly move in the opposite direction of the head, so searching and matching image macroblocks in the opposite direction of the head in the video data can achieve the best results. However, when the unmanned equipment turns and twists, the head of the unmanned equipment is inconsistent with the actual movement direction, and the efficiency of the above-mentioned search strategy will be greatly reduced. Therefore, it is necessary to adjust the matching strategy according to the actual operation of the unmanned equipment, that is, to calculate the relationship between the head of the unmanned equipment and the actual running direction according to the acceleration of the unmanned equipment in different directions, so as to modify the matching search strategy of different video frames in the video data.

[0082] In the Euler angles obtained above, It represents the deflection angle of the x-axis of the original coordinate system in the two coordinate systems. Since the x-axis in the original coordinate system represents the direction of the aircraft head, the Euler angle It mainly indicates the angle between the nose and the actual amount of movement. The larger the angle, the greater the heading change of the unmanned equipment during this attitude change, and the greater the deflection direction of the motion vector in the image frame collected by the unmanned equipment.

[0083] Euler Angles and Indicates the posture change of the unmanned equipment. When the Euler angle and The larger the value is, the greater the posture deflection angle of the unmanned equipment is. At this time, the greater the change in the shooting angle is, the greater the offset of the matching image block in the adjacent image frame is, so when matching in the video data, the matching offset should also be larger.

[0084] Based on the above analysis, the present invention analyzes the matching direction between image frames in the video data according to the Euler angle. The specific method includes steps S300 and S400.

[0085] S300: Obtaining a matching direction between image frames in the video data according to the yaw Euler angle.

[0086] Known Euler angles It mainly indicates the yaw of the unmanned equipment, that is, the change in the running direction of the unmanned equipment. Since the change direction of the image frame of the collected video data is opposite to the actual running direction of the unmanned equipment during the operation of the unmanned equipment, the motion vector of the image macroblock in the adjacent image frame of the video data collected by the unmanned equipment should be close to the opposite direction of the actual running direction of the unmanned equipment.

[0087] Get the current Euler angle of the unmanned device , where the Euler angle Taking the clockwise direction of the unmanned equipment's top-down perspective as the positive direction, the matching direction between image frames is calculated as:

[0088]

[0089] Where: The yaw Euler angle that indicates the change in the motion posture of the unmanned equipment; Indicates the matching angle between image frames of the current video data.

[0090] Make Angle The unit vector , the unit vector That is, the matching direction between image frames of the current video data.

[0091] S400: Analyze the offset vector of the image frame in the video data according to the rolling Euler angle and the pitching Euler angle, and obtain the correction matching direction between the image frames in the video data in combination with the matching direction.

[0092] When the unmanned device changes its posture, the lens carried on it will also cause the angle to deflect, so the shooting range and shooting center point in the shot video will change, so the overall image frame of the video data will change to a certain extent. Therefore, it is also necessary to combine the pitch Euler angle and roll Euler angle of the unmanned device to correct the actual matching direction.

[0093] Known Indicates the rolling Euler angle of the unmanned device. Represents the pitch Euler angle of the unmanned equipment. When the posture of the unmanned equipment changes, the shooting angle will change, that is, the center point of the image frame of the video data will change, which will also cause the overall movement of the image frame of the video data. This movement direction is opposite to the deflection direction of the Euler angle.

[0094] See also Figure 4 , which shows the basic process of a method for obtaining a correction matching direction provided by an embodiment of the present invention.

[0095] like Figure 4 As shown, according to the rolling Euler angle and the pitching Euler angle, the offset vector of the image frame in the video data is analyzed, and the correction matching direction between the image frames in the video data is obtained by combining the matching direction, including:

[0096] S401: Obtain the shooting parameters, shooting height and flight speed of the unmanned equipment.

[0097] Get the shooting parameters of the unmanned device, including: the focal length of the camera lens , the width of the camera lens And the width of the image frame in the acquired video data (pixel points). At the same time, the altimeter is used to obtain the current height of the unmanned equipment from the ground. , that is, the shooting height , and obtain the current flight speed of the unmanned equipment . Provide a data basis for subsequent analysis.

[0098] S402: Analyze the offset vector of the image frame in the video data caused by the pitch Euler angle according to the pitch Euler angle, combined with the shooting parameters and the shooting height, to obtain the pitch offset vector.

[0099] According to the pitch Euler angle, combined with the shooting parameters and the shooting height, the offset vector of the image frame in the video data caused by the pitch Euler angle is analyzed to obtain the pitch offset vector. Further, it includes:

[0100] First, according to the pitch Euler angle , combined with the shooting height , the actual change distance of the center point of the image frame in the video data is obtained, where the calculation formula of the actual change distance is:

[0101]

[0102] In the formula, Indicates the actual change distance of the center point of the image frame in the video data; Indicates the current shooting height of the unmanned equipment; Represents the pitch Euler angle The tangent function of .

[0103] Then, according to the actual change distance , combined with shooting parameters and shooting height , and the pixel change distance of the center point is obtained, where the calculation formula of the pixel change distance is:

[0104]

[0105]

[0106] In the formula, Indicates the pixel change distance of the center point; Indicates the actual change distance of the center point of the image frame in the video data; Indicates the ratio of pixel change distance to actual change distance; Indicates the current shooting height of the unmanned equipment; Indicates the lens width of the camera in the shooting parameters. Indicates the focal length of the camera lens in the shooting parameters. Indicates the width of the image frame in the video data collected in the shooting parameters ; Represents the ceiling function.

[0107] Then, the projection unit vector of the pitch Euler angle in the image frame is obtained. Specifically, the top of the image frame is taken as the nose direction, and the image frame is a top-down perspective, and the pitch Euler angle is obtained. Projected unit vector in the image frame , then the projected unit vector The opposite direction is the pitch Euler angle Resulting in an overall shift direction of the image frame.

[0108] Finally, the distance is changed according to the pixel and the projected unit vector of the pitch Euler angle , and the pitch offset vector is obtained. The calculation formula of the pitch offset vector is:

[0109]

[0110] In the formula, Denotes the pitch Euler angle The offset vector resulting in the image frame is the pitch offset vector; Indicates the pixel change distance of the center point; Denotes the pitch Euler angle The projected unit vector of .

[0111] S403: Analyze the offset vector of the image frame in the video data caused by the rolling Euler angle and the pitching Euler angle according to the shooting parameters and the shooting height, and obtain the rolling offset vector.

[0112] The same as the pitch offset vector calculation method, according to the rolling Euler angle and the pitch Euler angle, combined with the shooting parameters and the shooting height, the offset vector of the image frame in the video data caused by the rolling Euler angle is analyzed to obtain the rolling offset vector. Further, it includes:

[0113] First, according to the pitch Euler angle and the shooting height, the actual change distance of the center point of the image frame in the video data is obtained. This step is the same as in S402 and will not be repeated here.

[0114] Then, according to the actual change distance, combined with the shooting parameters and the shooting height, the pixel change distance of the center point is obtained. This step is the same as in S402 and will not be repeated here.

[0115] Then, the projection unit vector of the rolling Euler angle in the image frame is obtained. Specifically, the top of the image frame is taken as the nose direction, and the image frame is a top-down perspective, and the rolling Euler angle is obtained. Projected unit vector in the image frame , then the projected unit vector The opposite direction is the rolling Euler angle Resulting in an overall shift direction of the image frame.

[0116] Finally, the distance is changed according to the pixel and the projected unit vector of the rolling Euler angles , and the rolling offset vector is obtained, where the calculation formula of the rolling offset vector is:

[0117]

[0118] In the formula, Represents the rolling Euler angle An offset vector resulting in an image frame, namely a rolling offset vector; Indicates the pixel change distance of the center point; Represents the rolling Euler angle The projected unit vector of .

[0119] S404: Obtain a yaw vector according to the matching direction, combined with the flight speed and the update frequency.

[0120] First, according to the current flight speed of the unmanned equipment , and the update frequency of the flight control system of unmanned equipment , get the flight distance during a flight control system update ; Then, the flight distance of the unmanned equipment during a flight control system update process Convert to image frame distance ; Finally, the image frame distance of the unmanned equipment during a flight control system update process As matching direction The distance, the yaw vector of the unmanned equipment is .

[0121] S405: Combining the pitch offset vector, the roll offset vector and the yaw vector, obtain a correction matching direction between image frames in the video data.

[0122] Combining the pitch offset vector, the roll offset vector and the yaw vector, the correction matching direction between the image frames in the video data is obtained, further comprising: first, combining the pitch offset vector, the roll offset vector and the yaw vector to obtain the total offset vector, that is, the pitch Euler angle Resulting in the pitch offset vector of the image frame With rolling Euler angles Roll offset vector in the image frame and the yaw vector Perform vector addition to obtain the total offset vector between image frames in the video data Then preset a matching angle sequence. Since the pixel macroblocks in the image frame are arranged in a matrix, the angle for inter-frame matching cannot be selected arbitrarily. Therefore, the inter-frame matching angle sequence A=[0°, 22.5°, 45°, 67.5°, 90°, 112.5°, 135°, 157.5°, 180°, 202.5°, 225°, 247.5°, 270°, 292.5°, 315°, 337.5°]. Determine the closest angle of the total offset vector in the preset matching angle sequence, and use the closest angle as the correction matching direction between image frames in the video data, that is, the total offset vector obtained above In the above matching angle sequence Find the closest angle in , this angle That is, the correction matching direction between image frames in the video data.

[0123] S500: Match the image frames in the video data according to the corrected matching direction, and complete the video compression and upload to the cloud platform.

[0124] According to the correction matching direction, the image frames in the video data are matched, and the video compression and upload to the cloud platform are completed. Further: First, since the H264 video compression algorithm uses inter-frame compression for compression, and an important step in inter-frame compression is to search for similar image macroblocks in different image frames, it is necessary to divide the video data into macroblocks, that is, in the collected video data, each image frame is divided into several 8*8 macroblocks, and these macroblocks are used as basic data units to compress the video data. Then, according to the correction matching direction, the image frames in the video data are matched with macroblocks. After that, the video data after macroblock matching is compressed by the H264 compression algorithm. Finally, the compressed video data is uploaded to the cloud platform for users to watch and download.

[0125] Based on the same inventive concept as the above method, this embodiment also provides an unmanned equipment video transmission system based on a cloud platform.

[0126] A cloud platform-based unmanned equipment video transmission system includes: a data acquisition module, an Euler angle acquisition module, a matching direction analysis module and a video compression module. Among them:

[0127] A data acquisition module is used to collect video data acquired by unmanned equipment and to collect acceleration data of unmanned equipment;

[0128] The Euler angle acquisition module is used to obtain the Euler angle of the unmanned equipment's motion posture change based on the acceleration data. The Euler angle includes the yaw Euler angle, the roll Euler angle, and the pitch Euler angle.

[0129] A matching direction analysis module is used to obtain the matching direction between image frames in the video data according to the yaw Euler angle; and is used to analyze the offset vector of the image frame in the video data according to the roll Euler angle and the pitch Euler angle, and obtain the corrected matching direction between the image frames in the video data in combination with the matching direction;

[0130] The video compression module is used to match the image frames in the video data according to the correction matching direction, complete the video compression and upload it to the cloud platform.

[0131] Based on the same inventive concept as the above method, this embodiment also provides an unmanned device video transmission device based on a cloud platform.

[0132] A cloud platform-based unmanned equipment video transmission device, comprising a memory and a processor;

[0133] A memory for storing program codes;

[0134] The processor is used to read the program code stored in the memory, and execute to obtain the video data collected by the unmanned equipment, and obtain the acceleration data of the unmanned equipment; according to the acceleration data, the Euler angle of the change of the motion posture of the unmanned equipment is obtained, and the Euler angle includes the yaw Euler angle, the roll Euler angle, and the pitch Euler angle; according to the yaw Euler angle, the matching direction between the image frames in the video data is obtained; according to the roll Euler angle and the pitch Euler angle, the offset vector of the image frame in the video data is analyzed, and the correction matching direction between the image frames in the video data is obtained in combination with the matching direction; according to the correction matching direction, the image frames in the video data are matched to complete the video compression and upload to the cloud platform.

[0135] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0136] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for transmitting video of unmanned equipment based on a cloud platform, characterized in that: The method comprises: Obtain video data collected by unmanned equipment and obtain acceleration data of unmanned equipment; According to the acceleration data, the Euler angles of the motion posture change of the unmanned equipment are obtained, and the Euler angles include yaw Euler angle, roll Euler angle, and pitch Euler angle; According to the yaw Euler angle, obtaining a matching direction between image frames in the video data; Analyzing the offset vector of the image frame in the video data according to the rolling Euler angle and the pitching Euler angle, and obtaining the corrected matching direction between the image frames in the video data in combination with the matching direction; According to the corrected matching direction, the image frames in the video data are matched, and the video is compressed and uploaded to the cloud platform; Analyzing the offset vector of the image frame in the video data according to the rolling Euler angle and the pitching Euler angle, and obtaining the correction matching direction between the image frames in the video data in combination with the matching direction, including: Obtaining shooting parameters, shooting height and flight speed of the unmanned equipment; According to the pitch Euler angle, in combination with the shooting parameters and the shooting height, analyzing the offset vector of the image frame in the video data caused by the pitch Euler angle to obtain a pitch offset vector; According to the rolling Euler angle and the pitching Euler angle, in combination with the shooting parameters and the shooting height, analyzing the offset vector of the image frame in the video data caused by the rolling Euler angle to obtain a rolling offset vector; Obtaining a yaw vector according to the matching direction, in combination with the flight speed and the update frequency; Combining the pitch offset vector, the roll offset vector and the yaw vector, to obtain a correction matching direction between image frames in the video data; According to the pitch Euler angle, in combination with the shooting parameters and the shooting height, analyzing the offset vector of the image frame in the video data caused by the pitch Euler angle to obtain the pitch offset vector, including: According to the pitch Euler angle and in combination with the shooting height, an actual change distance of the center point of the image frame in the video data is obtained; According to the actual change distance, in combination with the shooting parameters and the shooting height, the pixel change distance of the center point is obtained; Obtaining a projection unit vector of the pitch Euler angle in the image frame; Obtaining a pitch offset vector according to the pixel change distance and a projection unit vector of the pitch Euler angle; According to the rolling Euler angle and the pitching Euler angle, in combination with the shooting parameters and the shooting height, an offset vector of an image frame in the video data caused by the rolling Euler angle is analyzed to obtain a rolling offset vector, including: According to the pitch Euler angle and in combination with the shooting height, an actual change distance of the center point of the image frame in the video data is obtained; According to the actual change distance, in combination with the shooting parameters and the shooting height, the pixel change distance of the center point is obtained; Obtaining a projection unit vector of the rolling Euler angle in the image frame; A rolling offset vector is obtained according to the pixel change distance and the projection unit vector of the rolling Euler angle.

2. The unmanned equipment video transmission method based on the cloud platform according to claim 1 is characterized in that: After collecting the video data acquired by the unmanned equipment, the method further includes: Dividing the video data into GOP groups to obtain GOP structure frame groups; Get the update frequency of the unmanned equipment flight control system; In the GOP structure frame group, the P frames are divided in combination with the update frequency, and each B frame is inter-frame compressed with the previous P frame.

3. The unmanned equipment video transmission method based on cloud platform according to claim 1 is characterized in that: Combining the pitch offset vector, the roll offset vector and the yaw vector to obtain a correction matching direction between image frames in the video data includes: combining the pitch offset vector, the roll offset vector and the yaw vector to obtain a total offset vector; Preset matching angle sequence; The closest angle of the total offset vector is determined in the preset matching angle sequence, and the closest angle is used as the correction matching direction between image frames in the video data.

4. The unmanned equipment video transmission method based on a cloud platform according to claim 1, characterized in that: The shooting parameters include: the focal length of the camera lens, the width of the camera lens, and the width of the image frame in the collected video data.

5. The unmanned equipment video transmission method based on cloud platform according to claim 1 is characterized in that: According to the correction matching direction, the image frames in the video data are matched, and the video is compressed and uploaded to the cloud platform, including: Dividing the video data into macroblocks; According to the corrected matching direction, performing macroblock matching on the image frames in the video data; The video data after macroblock matching is compressed using an H264 compression algorithm; The compressed video data is uploaded to the cloud platform.

6. A cloud platform-based unmanned equipment video transmission system, characterized in that: The system comprises: A data acquisition module is used to collect video data acquired by unmanned equipment and to collect acceleration data of unmanned equipment; An Euler angle acquisition module is used to obtain the Euler angle of the motion posture change of the unmanned equipment according to the acceleration data, and the Euler angle includes the yaw Euler angle, the roll Euler angle, and the pitch Euler angle; a matching direction analysis module, configured to obtain a matching direction between image frames in the video data according to the yaw Euler angle; and to analyze an offset vector of an image frame in the video data according to the roll Euler angle and the pitch Euler angle, and obtain a corrected matching direction between image frames in the video data in combination with the matching direction; Analyzing the offset vector of the image frame in the video data according to the rolling Euler angle and the pitching Euler angle, and obtaining the correction matching direction between the image frames in the video data in combination with the matching direction, including: Obtaining shooting parameters, shooting height and flight speed of the unmanned equipment; According to the pitch Euler angle, in combination with the shooting parameters and the shooting height, analyzing the offset vector of the image frame in the video data caused by the pitch Euler angle to obtain a pitch offset vector; According to the rolling Euler angle and the pitching Euler angle, in combination with the shooting parameters and the shooting height, analyzing the offset vector of the image frame in the video data caused by the rolling Euler angle to obtain a rolling offset vector; Obtaining a yaw vector according to the matching direction, in combination with the flight speed and the update frequency; Combining the pitch offset vector, the roll offset vector and the yaw vector, to obtain a correction matching direction between image frames in the video data; According to the pitch Euler angle, in combination with the shooting parameters and the shooting height, analyzing the offset vector of the image frame in the video data caused by the pitch Euler angle to obtain the pitch offset vector, including: According to the pitch Euler angle and in combination with the shooting height, an actual change distance of the center point of the image frame in the video data is obtained; According to the actual change distance, in combination with the shooting parameters and the shooting height, the pixel change distance of the center point is obtained; Obtaining a projection unit vector of the pitch Euler angle in the image frame; Obtaining a pitch offset vector according to the pixel change distance and a projection unit vector of the pitch Euler angle; According to the rolling Euler angle and the pitching Euler angle, in combination with the shooting parameters and the shooting height, an offset vector of an image frame in the video data caused by the rolling Euler angle is analyzed to obtain a rolling offset vector, including: According to the pitch Euler angle and in combination with the shooting height, an actual change distance of the center point of the image frame in the video data is obtained; According to the actual change distance, in combination with the shooting parameters and the shooting height, the pixel change distance of the center point is obtained; Obtaining a projection unit vector of the rolling Euler angle in the image frame; Obtaining a rolling offset vector according to the pixel change distance and the projection unit vector of the rolling Euler angle; The video compression module is used to match the image frames in the video data according to the correction matching direction, complete the video compression and upload it to the cloud platform.

7. An unmanned equipment video transmission device based on a cloud platform, characterized in that: The device comprises: a memory and a processor, wherein: The memory is used to store program codes; The processor is configured to read the program code stored in the memory and execute the method according to any one of claims 1 to 5.

Images