94 results about "Camera tracking" patented technology

The invention relates to a semantic simultaneous localization and mapping method and system based on Gaussian splashing. The method comprises the following steps: firstly, collecting a frame of RGB-D image, modeling a scene into a 3D semantic Gaussian field containing a plurality of 3D semantic gausses according to the RGB-D image, and rendering the 3D semantic gausses by using a tile rasterization technology to obtain 2D image plane gausses; rendering results of RGB color, depth and semantic features are extracted from the 2D image plane in a Gaussian mode, and the semantic features are decoded into semantic tags; constructing a mapping and tracking loss function by using an RGB color rendering result, a depth rendering result, a semantic tag and a truth value, and jointly optimizing a camera pose and a semantic Gaussian field based on a tracking stage and a mapping stage; and repeating the steps for each new frame of RGB-D image to complete the construction of the incremental semantic Gaussian map. Compared with the prior art, the method has the advantages of realizing robust camera tracking, real-time high-quality rendering, accurate 3D semantic reconstruction and the like.

A system for robot-assisted surgery includes a surgical robot having a robotic arm, an end effector coupled to the robotic arm, wherein the end effector is adapted to receive, translate, and orient a navigated surgical instrument; a camera tracking system adapted to intra-operatively track a pose of the navigated surgical instrument relative to a defined coordinate system; and a computer platform including a processor and a memory. In embodiments, the computer platform operative to display to a user an image of a target location on the patient and the pose of the navigated surgical instrument; and selectively control translation and orientation of the navigated surgical instrument based on a defined operational mode, to perform a surgical process under user control that comprises one or more of: reaming an acetabulum of the patient to a planned center of an acetabular prosthesis, or positioning the acetabular prosthesis in the reamed acetabulum.

The invention discloses a multi-camera collaborative pedestrian and vehicle cross-view tracking method and system, and relates to the technical field of intelligent monitoring. The method comprises the following steps: carrying out video stream acquisition on a monitoring area to obtain a multi-view video data set; multi-target detection of pedestrians and vehicles is carried out, tracking is carried out according to a plurality of detection targets, and a local tracking trajectory set of a plurality of cameras is generated; carrying out collaborative analysis on the plurality of cameras, constructing a multi-camera collaborative strategy to carry out cross-view trajectory matching on the local tracking trajectory set, and generating a global tracking trajectory set; and updating target states of the plurality of detection targets according to the global tracking trajectory set, and generating a multi-target cross-view tracking result of the pedestrian and the vehicle. The technical problem that in the prior art, information of different visual angles is difficult to integrate effectively in a multi-camera scene, so that target loss and track discontinuity easily occur in cross-camera tracking of pedestrians and vehicles is solved, and the technical effect of improving the continuity and accuracy of cross-camera tracking is achieved.

The invention discloses a double-layer dynamic probability SLAM (simultaneous localization and mapping) method for high-fidelity mapping in a dynamic environment, and belongs to the technical field of dynamic three-dimensional map building and positioning. The method comprises the following steps: a camera tracking module performs pixel-level dynamic probability estimation on input continuous image frames by using optical flow information and semantic tags, and optimizes and solves the camera pose of each frame of image through a probability weighting mechanism; the map building module converts the two-dimensional image into a three-dimensional map according to the camera pose of the frame, calculates the three-dimensional dynamic probability of each object in the image based on the two-dimensional dynamic probability graph of the frame, removes the object judged to be dynamic from the map, corrects the dynamic probability of the object in the image based on a feedback mechanism of a static map, and sends the corrected dynamic probability to the camera; and correcting and complementing the semantic tag of the object. According to the method, the adaptive capacity of a system to a dynamic scene can be remarkably improved, the dynamic artifacts are effectively eliminated while the tracking stability is ensured, and a static map reconstruction result with higher fidelity is obtained.

The invention relates to the technical field of computer vision and artificial intelligence, and discloses a public area pedestrian trajectory monitoring system based on cross-camera tracking and hybrid simulation completion. The system comprises a camera array module, a pedestrian detection and cross-camera tracking module, a monitoring blind area information base module, a hybrid drive pedestrian simulation engine module, a track fusion and complementation module and a simulation integration propulsion module. According to the invention, monitoring blind area tracks can be effectively filled, track continuity and prediction accuracy are improved, existing hardware is fully utilized to reduce cost, and modular design is easy to integrate and convenient to use. The generated complete track can be widely applied to scenes such as public safety monitoring, passenger flow analysis and emergency evacuation plan making in public places such as ports, subway hubs, cruise ship wharfs and commercial complexes, and supports a real-time monitoring or post-analysis mode.

The invention relates to the field of computer vision and navigation, and provides an SLAM acceleration method based on three-dimensional Gaussian rendering, and the method comprises the steps: initializing a three-dimensional Gaussian point cloud and a camera pose parameter based on input data, executing the camera tracking of a target frame in the input data, optimized camera pose parameters are output based on a staged switching strategy and an iteration mechanism, and camera tracking utilizes a floating point format with reduced precision; and executing a hierarchical screening mechanism in the optimized camera pose parameter to determine a key frame from the color image and the depth image, and performing mapping through a renderer supporting multichannel data by using the key frame and the optimized camera pose parameter to update the three-dimensional Gaussian point cloud. According to the method, through staged switching and iteration, pose optimization can be rapidly converged, a precision reduction floating point format is used, the numerical processing burden is relieved, a layered screening mechanism can be used for reducing the calculation cost lower than that of frame-by-frame fine comparison, and then the problem that the efficiency of an SLAM process is low is solved.

Methods provide computer-navigation assisted total hip arthroplasty (THA) procedures. Such procedures include the use of a navigated instrument, e.g., a navigated reamer construct or a navigated inserter construct to prepare the acetabulum and insert an acetabular shell, a camera tracking system adapted to track a pose of the navigated inserter or reamer construct relative to the patient in use, and a computer platform adapted to receive pose tracking information and generate and display navigational guidance for the user.

Conferencing systems and methods configured to generate true talker coordinates for use in camera tracking of talkers and objects in an environment and other room intelligence use cases are disclosed. The initial configuration and ongoing usage of conferencing systems can be improved by detecting and converting the locations of objects and talkers in an environment into a common coordinate system. The amount of time and effort by installers, integrators, and users, can be reduced leading to increased satisfaction with installation and usage of the conferencing system.

This application provides a camera tracking control system and intelligent care device, belonging to the field of intelligent elderly care technology. The system includes a motion drive module, a posture sensing module, a face recognition module, and a controller communicating with these three modules. The posture sensing module outputs corresponding drive signals based on the left and right displacement of the human body. The face recognition module outputs a stop signal after recognizing a face. The controller drives the camera to adjust its position according to the human body's movement, locking and recording upon face recognition. The camera tracking control system and intelligent care device provided by this invention can achieve fully automatic tracking and recording of the elderly, solving the problem of blind spots that are common with fixed cameras, effectively improving the reliability of home-based elderly care, and reducing the cost of manual care.

A surgical system for computer-assisted navigation during a surgical procedure includes at least one processor that obtains a 3D radiological representation of a target anatomy of a patient and a fiducial set of a registration fixture. An attempt is made to register a position of the fiducial set in the 3D radiological representation to a 3D imaging space tracked by a camera tracking system. Based on a determination that one fiducial of the fiducial set has an unsuccessful registration to a position of the 3D imaging space, the following operations are performed: displaying at least one view of the 3D radiological representation having a graphical overlay indicating that the fiducial has an unsuccessful registration to the 3D imaging space; receiving user-provided position information identifying where the fiducial is located in the 3D radiological representation; and registering the position of the fiducial to the 3D imaging space based on the user-provided position information.

The application discloses a multi-sensor fusion SLAM positioning method based on a direct method, and relates to the field of mobile robot positioning and navigation. The direct method is used for camera tracking by using the pixel point information with obvious gradient in an image, IMU pre-integration information is used as an initial pose, and the direct method is provided with an initial value. According to whether tracking is successful, the image frame is divided into a key frame and a non-key frame. A visual factor graph is constructed, an IMU residual term and a GPS residual term are inserted into the visual factor graph to construct a new fusion factor graph, and the optimization process of the system algorithm is completed through fusion factor graph optimization. A rear-end optimization strategy based on a sliding window optimization is used, the calculation complexity of rear-end pose optimization is fixed, a multi-sensor tight coupling fusion strategy is used, the advantages of marginalization are retained and the defects of marginalization are made up by using old information, and the system accuracy is improved. The system can work in a pure vision mode. Even if a GPS signal cannot be normally received, the system can continue to work in a vision inertial odometer mode.

The invention discloses a three-dimensional scene real-time reconstruction method fusing a symbol distance field and three-dimensional Gaussian representation. The method comprises the steps of firstly receiving a color-depth frame captured by a camera, obtaining a camera pose of a current frame through camera tracking estimation, then fusing and updating color and depth information of the current frame and a global symbol distance field, adaptively adding, optimizing and removing three-dimensional gauss, and finally correcting the color of a symbol distance field rendering result, so as to obtain a target image. And the reconstruction reality sense is improved. According to the invention, through fusion of three-dimensional Gaussian and symbol distance field representation, high-quality scene reconstruction can be realized by using a symbol distance field and a small amount of three-dimensional Gaussian, ultra-high-speed real-time reconstruction of a three-dimensional scene is realized, and high-precision geometry and high-quality textures are kept at the same time.

The present invention provides a system for monitoring and improving toothbrushing effectiveness. The system comprises a camera device comprising a camera or similar visual sensor configured to capture real-time footage of a user brushing their teeth an AI-powered software module is designed to analyse the footage using object recognition, pose estimation, and motion tracking algorithms to detect the user's hand, toothbrush, and face, a feedback device that comprises a feedback interface that provides real-time visual, auditory, or haptic feedback based on brushing technique, including parameters such as angle, coverage, and movement speed and movement patterns. Wherein the feedback provided comprises instructions to the user to alter their toothbrushing technique to bring the parameters closer to a predetermined set of ideal values. Thereby providing a system operates independently of sensors, accelerometers, or physical markers embedded in or attached to the toothbrush.

The invention discloses a semantic 3D Gaussian sputtering SLAM (Simultaneous Localization and Mapping) method based on illumination invariance. The method comprises the following steps: step 1, performing 3D Gaussian-based scene representation and joint micro-rendering on a to-be-constructed target area to obtain a multi-dimensional rendered initial scene model; 2, an internal appearance normalization IAN module is constructed, and decoupling of internal attributes of an initial scene model and transient illumination is achieved; 3, performing offset correction on a radiation field of a rendering graph in the initial scene model, and designing DRB-Loss loss to dynamically adjust correction intensity; step 4, through camera tracking optimization, combining a stable map and exposure compensation to realize robust pose estimation, and through double-stage key frame screening, improving SLAM system efficiency; step 5, constructing joint map loss, and optimizing all parameters of the 3D Gaussian primitive; and map updating is completed, invalid 3D Gaussian primitives are pruned, and a complete synchronous positioning and map building cycle is formed.

The invention provides a television program shooting system and method. The television program shooting system comprises a rendering display subsystem, a shooting synthesis subsystem and a director subsystem, wherein the rendering display subsystem comprises a large screen, a rendering server and a large screen processor; the shooting synthesis subsystem comprises a plurality of cameras, a camera tracking device and a synthesis server; the camera tracking device acquires camera tracking data, the rendering server forms a rendered image in real time according to the camera tracking data, and the large screen processor processes the rendered image and outputs the rendered image to the large screen for display; the camera captures a real image; the synthesis server expands the virtual scene outside the large screen of the real image to generate a synthesis image; and the video switching equipment switches and selects the composite image, and triggers the rendering server to perform camera position switching. And the video switching table switches the synthesis server to trigger the machine position switching of the rendering server, so that the technical problem of relatively poor support of multi-machine position switching of television program shooting in the prior art is solved.

Paving machines and paving machine control systems utilize sensors to identify the location and orientation of paving machines and corresponding attachments. The control system implements a design profile by automatically adjusting actuators. The control system receives transition values to calculate a smooth transition including continuously adjusting actuator values with reference to the location and orientation of the paving machine. The control system may identify resurfacing values to repair a damaged surface by identifying an offset value of an existing surface to an ideal surface with reference to a disposition of the paving machine to minimize material usage.

The application relates to the technical field of computer vision, and discloses a vehicle cross-camera tracking method and system based on a twin network, which comprises the following steps: collecting a track segment of a target vehicle under a camera; performing Kalman filtering on the track segment to obtain a motion state sequence, performing time series interpolation on the motion state sequence to obtain a speed fluctuation curve; constructing a directed connected graph based on the layout characteristics of the camera, mapping the speed fluctuation curve to the directed connected graph to obtain a topological behavior correlation graph of the target vehicle; jointly encoding the speed fluctuation curve and the topological behavior correlation graph to obtain a behavior feature vector of the target vehicle, and inputting the behavior feature vector into a twin network to obtain a behavior consistency score of the target vehicle; and associating the identity of the target vehicle based on the behavior consistency score, and determining that the target vehicle is the same target vehicle if the behavior consistency score is greater than a preset association threshold; and the application can improve the accuracy and robustness of vehicle cross-camera tracking.

A handheld three-dimensional (3D) measuring system is tracked using at least two camera tracking systems. Each camera tracking system has at least one motorized axis of rotation. The camera tracking systems use cameras to accurately measure the pose of the 3D measuring system based the position of visible targets on the 3D measuring system and the rotated angle of each camera tracking system.

A surgical system for computer assisted navigation during surgery, includes at least one processor that obtains a 3D radiological representation of a targeted anatomical structure of a patient and a set of fiducials of a registration fixture. The operations attempt to register locations of the set of fiducials in the 3D radiological representation to a 3D imaging space tracked by a camera tracking system. Based on determining one of the fiducials of the set has a location that was not successfully registered to the 3D imaging space, the operations display at least one view of the 3D radiological representation with a graphical overlay indicating the fiducial has not been successfully registered to the 3D imaging space, receive user-supplied location information identifying where the fiducial is located in the 3D radiological representation, and register the location of the fiducial to the 3D imaging space based on the user-supplied location information.

The invention provides a visual SLAM (Simultaneous Localization and Mapping) algorithm based on multi-scale neural tensor representation, which belongs to the technical field of indoor scene real-time reconstruction, and can efficiently capture the global structure and fine details of a scene by utilizing a tensor decomposition technology, and reduce the memory usage amount and the calculation overhead at the same time. In addition, the invention further introduces an efficient pixel-based color query method, and each pixel only needs neural network forward regression once in the method, so that the real-time performance of the neural radiation field-based SLAM (Simultaneous Localization and Mapping) is further improved. Experiments on a synthetic data set and a real data set show that the method is superior to the most advanced method in the aspects of reconstruction quality and camera tracking precision, and the efficiency in the aspects of running time and memory use is very high.

The invention relates to a wireless camera motion control method and device, computer equipment and a storage medium. According to the application, a complete closed loop of image acquisition, wireless transmission, upper computer processing and motion control feedback can be constructed, so that the camera can automatically perform motion adjustment according to the difference between the actual position and the expected position of the target in the three-dimensional space. According to the method, an image is obtained through an image sensor, preprocessed and then wirelessly sent to an upper computer, the upper computer calculates the three-dimensional pose of a target and generates a control instruction, and finally, a core processing unit drives a camera to complete actions, so that the target in a shot picture is always kept at a specified position. Wireless, real-time and adaptive camera tracking control is realized in the whole process, manual operation is greatly reduced, and target capturing stability and shooting precision are improved.

A camera tracking system receives patient reference tracking information indicating pose of a patient reference array tracked by a patient tracking camera relative to a patient reference frame. A local XR headset view pose transform is determined between a local XR headset reference frame and the patient reference frame. Remote reference tracking information is received indicating pose of a remote reference array tracked by a remote reference tracking camera. A remote XR headset view pose transform is determined between a remote XR headset reference frame of a remote XR headset and the remote reference array. A 3D computer image is transformed from a local pose determined using the local XR headset view pose transform to a remote pose determined using the remote XR headset view pose transform. The transformed 3D computer image is provided to the remote XR headset for display with the remote pose relative to the remote XR headset reference frame.

The present invention provides a system for monitoring and improving toothbrushing effectiveness. The system comprises a camera device 10 comprising a camera or similar visual sensor configured to cap

The application relates to a cross-camera vehicle tracking system and method based on license plate history sequence matching, and relates to a cross-camera vehicle tracking system and method. In order to solve the problem that license plate matching between different cameras is difficult in a large traffic network, especially in the case that a high-flow road section or multiple camera coverage areas overlap, license plate matching and vehicle tracking cannot be quickly and accurately performed, the application performs license plate recognition on each camera-captured video stream, takes all license plate recognition results of the same camera tracking vehicle as a sequence, performs Hungarian matching on license plate recognition history sequences of multiple cameras, and if the history license plate recognition sequences of two vehicles of different cameras can be matched, the two vehicles are considered to be the same tracking target. If the matching is successful and it is confirmed that the two vehicles are the same, the system will assign the same unique ID to the two vehicles, so as to realize continuous tracking across cameras. The application belongs to the technical field of computer vision.

The invention discloses a multi-target tracking method and device based on cross-camera trajectory association and a medium, for a target needing to be tracked, when the target appears in a video of a single scene for the first time, positioning is carried out, then the follow-up position of the target is predicted by combining the speed and the initial position of the target, and the follow-up position of the target is compared with that in an actual video to determine the target. And then, tracking targets across scenes and drawing a trajectory node space-time diagram, and associating trajectories in different scenes by using cosine similarity to realize multi-target tracking of cross-camera trajectory association. According to the invention, the actual moving tracks of the vehicle at different moments and different road sections can be visually displayed. Meanwhile, a correlation algorithm based on cosine similarity of a space-time diagram of track nodes is adopted, and track matching is carried out by using vehicle image blocks stored in the track nodes, so that the problem that a traditional cross-camera tracking method is sensitive to appearance changes of targets is effectively solved, and the accuracy and the real-time performance of cross-camera multi-target tracking are greatly improved.

The invention relates to a method for real-time multi-camera tracking of a target object comprising, for at least one new tracklet captured by at least one camera, calculating at least a first distance between the new tracklet and at least one reference tracklet belonging to the target object. The method also includes, when the smallest calculated first distance is between a first predetermined threshold value, called re-identification threshold, and a second predetermined threshold value, called human threshold, presenting the new tracklet to an operator, for the operator to assign or not assign the new tracklet to the target object, manually. The human threshold is a function of the number of reference tracklets in the reference list. The invention also relates to a computer program, to an object re-identification device and to an object re-identification system implementing such a method.

The utility model provides a torque test device of a cylindrical shell, which integrates a deformation measurement system based on a digital image correlation technology and a stereo camera tracking measurement technology into a high-temperature buckling test device of a thin-wall cylindrical shell structure. And the three-dimensional displacement and the full-field strain of the thin-wall cylindrical shell structure in the test process are dynamically monitored and displayed in real time. And processing the captured image by combining a digital image related technology to obtain the cylindrical shell structure modality at initial buckling, over-buckling and buckling failure moments in the whole buckling process. The thermal infrared imager integrated in the test device can realize the non-contact global monitoring of the temperature change condition of the thin-wall cylindrical shell structure, and can reliably realize the dynamic monitoring and real-time display of the temperature of the thin-wall cylindrical shell through the data acquisition-transmission-computer terminal. Therefore, the buckling performance and modal change of the thin-wall cylindrical shell under the coupling action of the thermal load and the mechanical load are explored, and the bearing capacity of the thin-wall cylindrical shell at high temperature is fully explored.

A multi-camera tracking system and a multi-camera tracking program are provided. [Solution] A multi-camera tracking system assigns the same tracking identification ID to the same person who appears in each of the images taken by the multiple cameras based on the images taken by the multiple cameras, and tracks the person to which the tracking identification ID has been assigned across the shooting ranges of the multiple cameras. The multi-camera tracking system further comprises a person determination means for determining, from among the people who appear in the images taken by the multiple cameras, people who belong to the majority when viewed from a predetermined viewpoint, and a person exclusion means for excluding people who are determined to belong to the majority by the person determination means from people who are targets of multi-camera tracking, and the ID assignment means assigns tracking identification IDs only to people who appear in each of the images taken by the multiple cameras and who have not been excluded by the person exclusion means.

The invention belongs to the technical field of image processing, and particularly relates to an image recognition system and an image recognition sensor applied to a camera, and the system comprises an image recognition module, a preprocessing module, a texture recognition module, an optical flow track module and a camera tracking module which are in communication connection in sequence. FPGA hardware acceleration is combined with redundancy reduction of particle screening, so that an image recognition system can stably perform full-link processing on a high-speed camera, and the non-delay tracking requirement of a high-speed moving target is met; through a texture channel fused by multiple edge channels, the edge integrity rate in a high-speed motion fuzzy scene is improved, and the tracking loss rate of light field particles is reduced; through a designed double-constraint optical flow mechanism, the optical flow estimation error of a high-speed moving target is reduced, the inter-frame position deviation of camera tracking is reduced, and accurate positioning of the high-speed target is realized, so that the problems of image precision reduction and tracking breakage caused by high-speed movement of the target in high-speed camera image recognition are solved.

To synchronize the position change of a camera for photographing the live action of an actor with a video displayed on a background digital screen in virtual production.SOLUTION: The computer system identifying a first position of the physical camera corresponding to a first time period, rendering a first virtual scene for the first time period, projecting the first scene onto a display surface to determine a first rendered image for the first time period, and receiving a first camera image of the display surface from the camera during the first time period; Determining a first corrected position of the camera by comparing the first rendered image and the first camera image, predicting a second position of the camera corresponding to a second time period, rendering a second virtual scene for the second time period, and projecting the second virtual scene onto the display surface to determine a second rendered image for the second time period.SELECTED DRAWING: Figure 9