139 results about "Aerial video" patented technology

The invention relates to the field of three-dimensional modeling, in particular to a live-action three-dimensional automatic modeling method and system based on an unmanned aerial vehicle. The method comprises the following steps: acquiring an aerial video of an unmanned aerial vehicle; motion blur convolution suppression processing and panoramic geometric stitching are performed on the unmanned aerial vehicle aerial video, so that a panoramic stitching reconstruction image is constructed; pixel-by-pixel deep semantic recognition is carried out on the panoramic splicing reconstruction image, so that an urban building area and a natural environment area are generated; performing dynamic light rendering evolution and building physical morphological structure analysis on the urban building area, and constructing a three-dimensional urban building rendering model; and carrying out vegetation type fine-grained identification on the natural environment region, carrying out three-dimensional panoramic fusion according to the three-dimensional city building rendering model, carrying out fuzzy region detection on the three-dimensional panoramic model, carrying out low-altitude secondary aerial photography, and extracting a low-altitude high-definition video of the fuzzy region. According to the invention, through clear and accurate three-dimensional modeling, the visual sense of reality and the spatial restoration degree of the live-action model are improved.

Processing circuitry may configure a system to implement a CAR-OnMap (“CAROM”) air framework for vehicle localization and traffic scene reconstruction using the aerial video of the traffic scene. Such a system may obtain aerial video of a traffic scene including vehicles that traverse the traffic scene and a satellite map image of the traffic scene as a distinct reference image. In such an example, processing circuitry may determine aerial image reference points within the aerial image which correspond to reference points in the satellite map image of the traffic scene. Processing circuitry may responsively generate calibrated images of the traffic scene from individual frames of the aerial video and determine unique keypoints on the vehicles in the traffic scene. In such an example, processing circuitry may track the vehicles across the individual frames of the aerial video utilizing the unique keypoints. Processing circuitry may output vehicle metrics for the vehicles.

The invention provides an unmanned aerial vehicle real-time road condition monitoring method and system and a medium, the method relates to the field of image data processing, and the system comprises an unmanned aerial vehicle which comprises an image acquisition device and a sensor group and is used for acquiring aerial videos and flight parameters of the unmanned aerial vehicle in real time; the streaming media server is used for receiving and storing the aerial video transmitted by the unmanned aerial vehicle; analyzing the video stream into a frame-by-frame image sequence with aligned timestamps; performing target detection on each frame of image, and identifying a target vehicle by using a pre-trained deep learning model; carrying out target tracking on the target vehicle in the continuous frames based on an intersection-to-union ratio matching and trajectory prediction algorithm, and constructing a target motion trajectory; and calculating the displacement distance of the target vehicle in the image based on an optical flow method, feature point matching and a deep learning algorithm, and estimating the actual running speed of the vehicle in combination with the flight parameters of the unmanned aerial vehicle. According to the system, computer vision and sensor technologies are combined, and accurate speed measurement is realized through target detection, tracking and speed estimation.

The invention relates to the field of urban road modeling, in particular to an aerial photography data processing method and system for urban road modeling. The invention discloses an aerial photography data processing system for urban road modeling. The aerial photography data processing system comprises an aerial photography video acquisition module, a road modeling module, a photogrammetry module, a spatial registration module and a rendering synthesis module. According to the invention, on the basis of a spatial calibration mechanism of the original aerial image and the BIM model, redundant processes such as point cloud acquisition, data fusion and manual correction are eliminated, and linear processing from data acquisition to dynamic result output is realized; according to the architecture, the hardware resource dependency and the operation complexity are greatly reduced, and designers are endowed with the capability of completing large-scale scene visualization processing in a conventional engineering environment; according to the method, a transmission chain from original data to decision support is remarkably shortened, and important engineering scheme deduction and dynamic review have unprecedented timeliness.

The invention relates to the technical field of intelligent traffic monitoring, in particular to a vehicle identification and traffic incident detection method and system based on the view angle of an unmanned aerial vehicle, and the method comprises the steps: obtaining the aerial traffic video data of the unmanned aerial vehicle and the flight control data of the unmanned aerial vehicle; performing target identification on the image in the video data by adopting a target detection algorithm to obtain vehicle information; tracking the vehicle in the video data by using a target tracking algorithm, and mapping the identified vehicle to a unified coordinate system in combination with the flight control data to generate vehicle trajectory data; constructing a comprehensive road description model based on the vehicle trajectory data and the vehicle information; and forming a traffic incident recognition module based on the comprehensive road description model, and recognizing the input aerial video according to a preset traffic incident recognition rule. According to the invention, by optimizing the vehicle identification algorithm, constructing the road description model and designing the efficient traffic event identification module, the application efficiency of the unmanned aerial vehicle aerial video in the traffic monitoring field is effectively improved.

The invention relates to the technical field of aerial video analysis, and discloses a large-scene multi-modal analysis system and method based on an unmanned aerial vehicle. According to the method, an original video frame sequence is obtained from aerial photography equipment, a scene change period and an object motion trend are extracted by calculating inter-frame motion feature vectors, and whether a scene is in a stable or dynamic state is judged by means of a state classification model. Calculating a tracking target position according to preset parameters in a dynamic state, and adjusting and analyzing a target area in combination with a motion trend; generating a camera parameter adjustment instruction according to the deviation value of the target area and the actual object position, and outputting the camera parameter adjustment instruction to an execution mechanism; acquiring a complexity value through the scene complexity feedback signal, updating an analysis strategy by adopting an adaptive algorithm when the complexity value exceeds a preset range, and outputting an adjustment signal; the output time sequence of control and strategy adjustment signals is optimized, meanwhile, the frame sequence is monitored in real time, the parameter change trend is analyzed, the preset parameters are dynamically updated to meet the user requirements, and efficient video analysis processing is achieved.

The invention discloses an unmanned aerial vehicle visual angle multi-target tracking method and system based on improved ByteTrack, and belongs to the technical field of target tracking, and the method comprises the steps: training a target detection algorithm, and carrying out the target detection of a public data set through employing the trained target detection algorithm; setting a high-score confidence threshold and a low-score confidence threshold, classifying detection frames in the target detection result, and dividing the detection frames of the target detection result into high-score detection frames and low-score detection frames; an improved ByteTrack multi-target tracking algorithm is adopted, a shielding matching module is introduced, and target matching is carried out on a high-score detection frame and a low-score detection frame for three times; and updating all successfully matched track frames based on a matching result, reserving a preset frame number of unmatched track frames for subsequent frame matching, and outputting a tracking result of the current frame. The method improves the tracking accuracy and robustness, and is suitable for the multi-target tracking task in the aerial video of the unmanned aerial vehicle.

[Problem] To provide a show window that has an effect of providing a video seemingly popping out directly from a wall and with which the ability to pull in customers can be expected to be enhanced.　The show window comprises: a window in a wall surface; and an aerial video display device provided to the inside of the window. The aerial video display device projects an aerial video on the outside of the window. The aerial video display device, which is formed from a to-be-projected body that constitutes a basis for the aerial video and a retro-transmissive optical plate that is interposed between the to-be-projected body and the window at a certain angle, is capable of projecting the aerial video through a transparent plate fitted into the window. In one embodiment, a darkening sheet for maximally suppressing reflection and scattering of light is provided to a space on the inside of the window at which the aerial video display device is provided.

The invention relates to an unmanned aerial vehicle aerial video vehicle robust tracking method in an anti-shielding scene, and the method comprises the steps: obtaining a road traffic video through the fixed visual angle high-altitude shooting of an unmanned aerial vehicle; marking a specific area in the video frame based on the polygon mask, and generating coordinate points of a polygon area; performing target detection on the video frame based on a pre-trained target detection model, and outputting a vehicle detection frame and category information; through adaptive target tracking, shielding area tracking is carried out on video vehicles in a shielding area, non-shielding area tracking is carried out on video vehicles in a non-shielding area, and a vehicle tracking trajectory with a stable ID and a flow statistical result are obtained; and matching a lane for each video vehicle, and outputting a vehicle tracking trajectory with a stable ID and a traffic statistical result, wherein the vehicle tracking trajectory has a serial number of the lane where the tracked vehicle is located. Compared with the prior art, the problems that the vehicle cannot be continuously tracked and the tracking precision is low due to the shielding object are solved.

The invention discloses a grid-coding-based video space-time retrieval method and device, the grid-coding-based video space-time retrieval method is executed in computing equipment, and the method comprises the following steps: mapping a coordinate range of a target area into a corresponding grid code set according to a Beidou grid standard on the basis of the coordinate range of the target area; acquiring video data with an intersection or inclusion relationship between the spatial range of the shot object and the target area; combining the shooting time of any video data with each grid code to generate a space-time grid code set; constructing an index structure corresponding to the video data by taking each time-space grid code in the time-space grid code set as a main key; and in response to query information of the user, analyzing a space-time range in the query of the user, mapping the space-time range into a corresponding space-time grid code range, executing retrieval based on the range, and returning hit video data. According to the method, rapid positioning and accurate retrieval of large-scale aerial photography video data are realized.

The invention provides an unmanned aerial vehicle aerial video playback management system based on space-time fusion, and the system carries out the space-time fusion of the flight parameters and holder parameters of an unmanned aerial vehicle and the information of an aerial video, and carries out the query and playback of the aerial video according to the time and geographic position. The system comprises a data access module, an analysis processing module, a storage management module and a query playback module. According to the method, space-time fusion processing is carried out on the flight parameters, the holder parameters and the video data of the unmanned aerial vehicle, and query and playback of historical videos according to time and geographic positions are supported. Compared with a traditional management system, the system can make full use of aircraft and load parameter information, analyzes a video aerial photography area, and realizes video query and retrieval based on a time axis and a spatial range through association fusion of time and spatial domains.

The invention discloses an unmanned aerial vehicle aerial video language positioning method in a disaster rescue scene, and the method comprises the steps: obtaining unmanned aerial vehicle aerial videos of a plurality of continuous frame images and a natural language description text of a to-be-positioned target, and jointly inputting the unmanned aerial vehicle aerial videos and the natural language description text into an unmanned aerial vehicle aerial video language positioning system, thereby obtaining a language positioning result; the unmanned aerial vehicle aerial video language positioning system comprises a video text feature extractor, a multi-modal multi-scale spatial-temporal feature coding module, a query modulation module and a multi-scale perception coordinate dynamic reasoning decoding module. And finally, outputting updated target bounding box coordinates through a multi-scale perception coordinate dynamic inference decoding module for representing the spatial position of the target referred by the natural language description text in the image. According to the method, deep semantic analysis and context understanding can be carried out on aerial video contents, and the practicability and efficiency of the unmanned aerial vehicle in security rescue tasks are remarkably improved.

The invention relates to the field of photogrammetric video and vector file fusion, in particular to an unmanned aerial vehicle flight video superposition and vector file real-time fusion method, which comprises the following steps of: 1, acquiring data; 2, resampling a vector range line; 3, decoding the aerial photography video stream; 4, comparing the coordinates; step 5, intersection extraction; step 6, image rendering; 7, for each frame of image of the video stream, the step 4, the step 5 and the step 6 are repeated in sequence; and step 8, encoding the image into a video stream, and realizing fusion display of the vector range line and the video. According to the scheme, on the basis of oblique photogrammetry and computer video, the method for fusing the real-time video and the vector range line in aerial photography of the unmanned aerial vehicle is designed, and the video and the vector range line are fused in a real sense.

The invention relates to a photovoltaic power station construction progress monitoring method based on unmanned aerial vehicle aerial video, and the monitoring method comprises the following steps: S1, building stage division and data set establishment; s2, improving a YOLOv8 target detection model; s3, model training and key component detection; s4, counting key components based on the video; s5, construction stage determination and progress calculation; the construction process of the photovoltaic power station is analyzed, the target detection algorithm is improved, the key components in the construction process of the photovoltaic power station are detected, the construction progress information of the photovoltaic power station of the target land parcel is obtained according to the type and the number of the detected key components, visualization, refinement, standardization and intelligentization of construction management of the photovoltaic power station are achieved, and the construction efficiency of the photovoltaic power station is improved. The construction quality and comprehensive benefits of a photovoltaic power station project are effectively improved, the problem that the construction progress statistical efficiency of an existing photovoltaic power station is low is solved, and the method has great significance in promoting digital and intelligent management of the photovoltaic power station project.

The invention belongs to the technical field of computer vision and digital media, and discloses a dome-screen film production method and system based on a high-altitude aerial image. Projecting the multi-view aerial video sequence to a unified spherical coordinate system, and constructing a panoramic space with an overlapping region; performing non-rigid geometric deformation processing on the overlapping region of the panoramic space to generate an intermediate image with aligned pixels; calculating the fusion cost of each pixel point in the overlapping region in the intermediate image, and performing path search based on the fusion cost of each pixel point to generate a dynamic suture line; generating an image mask based on the dynamic suture line, performing multi-scale frequency domain adaptive fusion on the intermediate image by using the image mask to generate a fused panoramic image, and remapping the fused panoramic image into a projection format adaptive to dome screen playing to output; and the real reducibility and the manufacturing quality of the dome film are greatly improved.

The invention relates to the technical field of unmanned aerial vehicle communication, and particularly discloses a multi-antenna unmanned aerial vehicle communication energy consumption minimization method and system.The method comprises the steps that firstly, an aerial video monitoring system based on a multi-antenna rotor unmanned aerial vehicle is constructed, and a multi-antenna unmanned aerial vehicle (UAV) is allowed to provide services for a plurality of ground users (GU) at the same time; then, through joint optimization of the flight path, the flight time and transmitted beam forming of the UAV, on the premise that the QoS requirement of a user is met, an optimization problem is constructed by taking minimization of the total energy consumption of the UAV as an optimization target, and the optimization problem is further solved. In order to solve the optimization problem, firstly, a path discretization method is combined with a golden section search method to determine the flight time and the flight path of the UAV, so that the propulsion energy consumption of the UAV is minimized, and then the communication energy consumption of the UAV is minimized. Simulation results show that the method and the system are remarkably superior to an existing reference scheme in the aspect of energy consumption, and high efficiency and practicability are shown.

The invention provides an aerial video image target tracking method and system based on broken trajectory repair, and the method comprises the steps: inputting an aerial video image into a sliding window slicing module frame by frame, and segmenting each frame of image into a plurality of image slices P1-Pn; respectively inputting the original images P0 and P1-Pn of each frame into a trained joint detection-tracking model, wherein the model comprises a target detection network and a Re-ID network integrated with a broken trajectory prediction and restoration algorithm; the target detection network carries out target detection on P0-Pn; and the Re-ID network performs target tracking according to the target detection result of each target of each frame: initializing the detection frame coordinate of each target of the first frame into a target trajectory, matching the detection frame coordinate of each target of the current frame with the existing target trajectory by combining the ID identity vector from the second frame, and if the matching succeeds, performing target tracking. And updating the detection frame coordinate of each target of the current frame to the target track, and if the matching is not successful, creating a new target track. According to the invention, target tracking can be carried out on aerial video images.

The invention discloses a traffic state recognition method and system considering vehicle space characteristics, and the method comprises the steps: extracting the initial vehicle trajectory data of a target vehicle from an aerial video, and obtaining the road calibration information; according to the initial vehicle trajectory data and the road calibration information, more accurate target vehicle trajectory data are obtained through calculation; according to the target vehicle trajectory data, constructing multi-dimensional spatial feature parameters; and performing traffic state recognition according to the spatial feature parameters to obtain a traffic state recognition result. The method can achieve the precise recognition of the traffic state, and can be widely used in the technical field of intelligent traffic.

The embodiment of the invention provides a live-action pipeline reverse video generation method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring an aerial video, video POS (Point Of Sale) data, camera parameters and pipeline geographical coordinates; wherein the aerial video comprises a plurality of video frames; according to the POS data and the camera parameters, constructing a corresponding relation between geographic coordinates and video frame coordinates; calculating to obtain pipeline video frame coordinates corresponding to the pipeline geographical coordinates according to the pipeline geographical coordinates and the corresponding relation; and superposing the pipeline video frame coordinates to the video frames to obtain a live-action pipeline reverse video. According to the embodiment of the invention, the corresponding relation between the geographic coordinate and the video frame coordinate is constructed, and the data with the geographic coordinate attribute of the live-action pipeline is added in the aerial video of the unmanned aerial vehicle, so that the ground condition along the pipeline is more intuitively presented in the aerial video, and pipeline inspection, rescue and relief work and integrity management are more facilitated.

The invention discloses a city building change detection method based on unmanned aerial vehicle videos and a three-dimensional model, and the method comprises the steps: obtaining multi-stage unmanned aerial vehicle aerial video data of a target region, taking a city building base three-dimensional model of the target region as a reference, and carrying out the uniform frame extraction of the multi-stage unmanned aerial vehicle aerial video data, generating a multi-stage urban building three-dimensional model; the urban building base three-dimensional model is constructed based on unmanned aerial vehicle oblique photography data of a target area; generating dense point clouds of the multi-period urban buildings based on the multi-period urban building three-dimensional model; and carrying out change detection on the dense point clouds of the multi-period urban buildings, and extracting urban building change pattern spots. The method solves the problems that the existing unmanned aerial vehicle oblique photography reconstruction of the three-dimensional model is high in cost and slow in updating, and rapid urban building change detection cannot be carried out.

To provide a display device capable of displaying an aerial image at a wide viewing angle.SOLUTION: An aerial video display device 100 according to the present invention includes: a plurality of light sources 110_1, 110_2, 110_3 that output the same video, respectively; a retroreflection sheet 120 including a first retroreflection surface 120_1, a second retroreflection surface 120_2, and a third retroreflection surface 120_3 facing the plurality of light sources; and a beam splitter 130 located so as to face the retroreflection sheet 120. Each of the first, second and third retroreflection surfaces 120_1, 120_2, 120_3 forms therein a plurality of notches 122 for letting the video of the light source 110 pass through or pass by, and a plurality of aerial images 150_1, 150_2, 150_3 corresponding to the plurality of light sources 110_1, 110_2, 110_3 are displayed.SELECTED DRAWING: Figure 3

Provided is a new radio control device for controlling a radio control object.　Here, as an example of the radio control device, a radio control device for an unmanned aerial vehicle including an aerial video display device is shown. An imaging device of the unmanned aerial vehicle transmits a video captured from the sky to the aerial video display device. The aerial video display device converts the video captured by the unmanned aerial vehicle into a video viewed from the viewpoint of overlooking the unmanned aerial vehicle from the sky, superimposes an image indicating the unmanned aerial vehicle on the converted video, and then displays same as an aerial video. The user pilots the unmanned aerial vehicle by manually manipulating the image of the unmanned aerial vehicle displayed in the aerial video using gestures.

The present invention relates to the field of unmanned aerial vehicle navigation technology, and in particular to a map matching navigation method based on decision analysis. The method comprises the following steps: searching for corresponding environmental data in a preset map database according to the acquired positioning information; extracting an initial aerial image sequence from the acquired initial aerial video, performing lens distortion correction on the initial aerial image sequence, and obtaining a standard aerial image sequence; performing contour extraction on the standard aerial image sequence, and obtaining a standard environmental contour; performing overlap matching on the environmental data, and obtaining overlap environmental data; performing data correction on the overlap environmental data, and obtaining navigation environmental data; and performing position matching on the navigation environmental data using a preset displacement bag-of-words model. The present invention also proposes a map matching navigation device, an electronic device, and a storage medium based on decision analysis. The present invention can improve the accuracy of unmanned aerial vehicle map navigation.

The present invention relates to a server and method for super-resolution that may vary a super-resolution method for video data (e.g., satellite image, aerial video, drone video, etc.) according to a user's request, and a system including the same. The super-resolution server may include a data collection module that receives video data and requirement information related to the user's needs for the video data, a super-resolution module that super-resolves the video data according to the requirement information to generate a high-resolution satellite image, and an output module that outputs the high-resolution satellite image and reliability information on the high-resolution satellite image.

The invention provides an AR superposition method for a CAD road drawing and an unmanned aerial vehicle aerial video, and the method comprises the following steps: S1, converting the coordinates of the CAD road drawing into latitude and longitude data, and obtaining the elevation information of the drawing; s2, latitude and longitude data and elevation data are extracted from each frame of image of the unmanned aerial vehicle aerial video; s3, establishing connection between the CAD road drawing and the unmanned aerial vehicle aerial video by using the CAD road drawing, the unmanned aerial vehicle aerial video and common known information of the latitudes, longitudes and elevations of the CAD road drawing and the unmanned aerial vehicle aerial video, and realizing projection of the CAD road drawing on the unmanned aerial vehicle aerial video; and S4, finally, all the projected points are connected according to the previous connection mode on the CAD road drawing so as to restore the drawing. According to the AR superposition method of the CAD road drawing and the unmanned aerial vehicle aerial video, rapid and fully-automatic superposition is realized by using information contained in the CAD road drawing and the unmanned aerial vehicle aerial video, so that road construction progress supervision and progress reporting are facilitated.

The invention belongs to the technical field of aerial video editing, and particularly discloses an aerial video AI automatic editing method and system fused with humanity elements, and the method comprises the following steps: receiving aerial materials uploaded by a user, and providing a video template library containing a plurality of scenic spot IPs and humanity elements for the user for selection, wherein each video template is associated with a humanity attribute tag and a technical parameter of a specific scenic spot; based on the video template selected by the user, performing multi-dimensional AI processing on the aerial photography material, including background music matching, subtitle generation, explanation speech synthesis, transition effect addition and aerial photography material embedding; and integrating the processed aerial photography materials according to the sequential logic of the template to generate a complete aerial photography video clip. According to the method, the scenic spot IP and the humanity element are integrated, full-process AI automatic editing of the aerial video can be realized, and the requirements of a user on efficient and high-quality humanity aerial video production are met.

The present application belongs to the field of drone inspection data processing technology, and in particular relates to a distribution construction project model association method based on drone inspection. It includes the following steps: obtaining aerial video images based on drone inspection; establishing a dynamic engineering model of the distribution construction project; visual processing of the dynamic engineering model of the distribution construction project; establishing an association model between the inspection camera position coordinates and the navigation perspective coordinates; establishing a camera position coordinate association model; establishing an inspection camera position coordinates and an optical perspective association model between the navigation perspective; The distribution construction project model association method based on drone inspection in the present application is mainly used to realize adaptive synchronous tracking of the dynamic engineering model with the inspection video during the planning and execution of the distribution construction project, and to realize synchronous acquisition of the model corresponding image data with the inspection video perspective, so as to facilitate the purpose of comparative analysis.

An aerial video display device according to the present invention comprises a first aerial display unit (DU1) and a second aerial display unit (DU2). The first aerial display unit (DU1) includes a first retroreflective material (11A), a first beam splitter (12A), and a first display (13A), and is configured to display a first aerial image (14A) at a position on the first display (13A) in plane symmetry with respect to the first beam splitter (12A). The second aerial display unit (DU2) includes a second retroreflective material (11B), a second beam splitter (12B), and a second display (13B), and is configured to display a second aerial image (14B) at a position on the second display (13B) in plane symmetry with respect to the second beam splitter (12B). The first aerial display unit (DU1) and the second aerial display unit (DU2) are disposed such that the first aerial image (14A) and the second aerial image (14B) are displayed at the same position.

1. Name of the product in this design: Unmanned Aerial Vehicle (UAV). 2. Purpose of this design: To mount a gimbal camera for aerial video or photograph shooting, etc. 3. The key design features of this product are its overall shape. 4. The image or photograph that best illustrates the design's key points: 3D rendering 1.

The present invention provides a multimodal aerial video vehicle target tracking method that integrates scene prior knowledge, including the steps of associated region of interest extraction, local image edge detection, local image main color extraction, appearance weight vector calculation, scene prior information library construction, next frame target state variable prediction and target association result output. The method fully exploits the multimodal small target features, fully considers the temporal and spatial constraints between frames, and makes full use of scene prior information. The obtained target tracking result is more accurate, solves the difficulty of target tracking, namely the ID confusion problem, realizes stable and accurate aerial video vehicle target tracking, and is used to construct a real and accurate vehicle driving trajectory, extract traffic parameters from the trajectory, provide real and effective data support for intelligent vehicle research, lay the foundation for data-driven intelligent vehicle research methods, and support research in the fields of intelligent vehicle perception, decision planning, control, testing, etc.