432results about How to "Improve tracking efficiency" patented technology

The embodiment of the invention provides a train operation control system. The system comprises that a train operation plan is generated, issued and adjusted by a train automatic control system; high-precision train autonomous positioning is realized by a vehicle-mounted controller through correction of a train autonomous positioning system and a trackside transponder; a trackside controller receives commands which are transmitted by the vehicle-mounted controller and used for operating trackside equipment and controls the corresponding trackside equipment to actuate and lock to the corresponding position according to the command requirements; and a data communication subsystem performs data communication with each set of ground equipment via a redundant backbone network and realizes wireless transmitting and receiving of trackside controller information and vehicle-mounted controller information via a wireless communication antenna. CI and ground ATP equipment are reduced and WCU equipment is increased, and mutual resource coordination is performed via a mode of direct communication between adjacent trains and between the trains and the WCU so that system cost is reduced and train tracking efficiency is enhanced.

The invention discloses a video monitoring system and a video monitoring method. Direction of a pan-and-tilt camera is adjusted according to received pan-and-tilt control commands, and the pan-and-tilt camera acquires front-end videos and outputs the same to a pan-and-tilt camera path. A monitoring platform feeds the pan-and-tilt camera path back to a client side and tracks a policy list automatically after performing access authentication on the client side, and outputs received pan-and-tilt control commands to the pan-and-tilt camera after performing control authentication on the received pan-and-tilt control commands. The client side selects an automatic tracking policy from the automatic tracking policy list, packages presetting-bit commands in the pan-and-tilt control commands and outputs the pan-and-tilt control commands to the pan-and-tilt camera; and according to the acquired pan-and-tilt camera path, real-time videos are downloaded to play, and according to the played videos, a target object is positioned, and the position of the target object at the next calculating time is predicted and packaged in the pan-and-tilt control commands to transmit. By the video monitoring method, tracking efficiency can be improved while monitoring cost is reduced.

The invention discloses a moving object tracking method in a video sequence image, and belongs to the technical field of image processing. In order to solve the defects that the Kalman filter tracking success rate in the prior art is relatively low and the particle filtering real-time performance is poor, real-time performance of the particle filter algorithm is researched, characteristic matching is performed according to the moving object image and the color template, the particle filter tracking is improved by combining foreground object detecting, the particle filter algorithm based on the foreground detecting is improved, crossed shielding judgment is introduced, a state transfer equation is established, moving object tracking is completed, reliability and variety of particles are improved, the moving state of the object is described well, the algorithm real-time performance is improved when the calculation amount is reduced, re-sampling is stopped during crossing, so that the particles around the target are not interfered.

The invention discloses a 3D virtual set ray tracking method for accelerating back light source irradiation, belonging to the technical field of realistic 3D virtual set drawing. Currently, the Monte Carlo ray tracking method is usually used for drawing the 3D virtual set irradiated by back light source. According to the Monte Carlo ray tracking method, as multiple light source sampling point visibility calculations need to be carried out, computational efficiency is not high. In the invention, data concerning depth of a geometric surface patch irradiated by an area light source is obtained by a precomputation process; and in the process of ray tracing process, the depth data are used for calculating light source sampling point visibility at each scene point, computations such as creation, ergodic and intersection test of visibility testing light rays are avoided and light ray tracking efficiency is improved. Compared with the Monte Carlo ray tracking method, the method in the invention can increase ray tracking speed by 3-4 times.

The invention discloses a method for tracking an infrared small target based on sparse representation and transfer limited particle filtering. The method includes the following steps: first, introducing a blocking binary indication vector representing a normal target region and a noise background outlier region, and building a sparse representation model of an infrared small target according to atarget dictionary template; then, extracting a high-frequency region of an infrared image through saliency detection as prior information in the state transition process of a particle filter model, and predicting the state of the target and sampling particles under the limit; and finally, building a particle filter observation model based on target sample particle sparse reconstruction error difference, and estimating and tracking the state of the target according to an online template update strategy. The state estimation ability of random particles is enhanced, and the adaptability and tracking accuracy of particle sparse representation to small and weak moving targets are improved.

The invention discloses a self-adaptive feature fusion-based multi-scale correlation filtering visual tracking method. The method comprises the following steps: firstly, the correlation filtering is carried out on a target HOG feature and a target color feature respectively by using a context-aware correlation filtering framework; the response values under the two features are normalized; weightsare distributed according to the proportion of the response values and then are subjected to linear weighted fusion, so that a final response graph after fusion is obtained; the final response graph is compared with a pre-defined response threshold value to judge whether the filtering model is updated or not; finally, a scale correlation filter is introduced in the tracking process, so that the scale adaptability of the algorithm is improved. The method can be used for tracking various features. The performance advantages of the features are brought into play, and a model self-adaptive updating method is designed. In addition, a precise scale estimation mechanism is further introduced. According to the invention, the updating quality and the tracking precision of the model can be effectively improved, and the model can be changed in scale. The method is good in robustness under complex scenes such as rapid movement, deformation, shielding and the like.

The invention discloses a Bernoulli smoothing weak target detection and tracking method under thresholding measuring. The method mainly solves the problems that in the prior art, the weak and small target tracking efficiency is low, the tracking performance is not ideal, and the computing computation complexity is high under the condition of the low signal-to-noise ratio. The method includes the steps that firstly, a measuring threshold value is set, indexes of pixel points exceeding the measuring threshold value in grayscale image data are extracted, and an index set serves as a measuring set to be stored; secondly, the set measuring threshold value is utilized, and the detection probability of all the pixel points in the grayscale image is computed; thirdly, the measuring likelihood is computed according to the stored measuring set and the detection probability of the pixel points; lastly, a target is detected and tracked through Bernoulli smoothing. By means of the method, under the condition of the low signal-to-noise ratio, the tracking efficiency and the tracking accuracy of weak and small targets can be improved effectively, and the computation complexity and storage space are lowered.

The invention discloses an intelligent transportation moving object detection tracking method which is used for detecting and tracking a moving object in an intelligent transportation video. The intelligent transportation moving object detection tracking method comprises the following steps: considering objects with obvious edge characteristics such as guard bars in the middle part and on the two sides of a road in a video frame image; adopting a finite difference first-order partial derivative matrix to calculate the gradients of an input front video frame image and a back video frame image, and extracting a fine outline of an input image characteristic area; performing outline connection, area filling consolidation and morphological processing to obtain a preprocessed image; adopting an improved SIFT algorithm to extract key points from the preprocessed image, and only establishing a six-layered Gaussian pyramid for the preprocessed image, so as to ensure the situation that a few of key points can be detected when the image is changed in a small scale, meanwhile reduce redundant calculation requirement on establishing the pyramid, and improve the time efficiency of the algorithm; before frame difference, the image of the video sequence front frame and back frame is rectified by utilizing an affine transformation model obtained by the preprocessed image, so as to eliminate the influence of the video frame shift on performance detection.

The invention relates to the technical field of image processing, in particular to a target tracking method, a target tracking device, a computer readable medium and electronic equipment. The method comprises the steps of obtaining a to-be-tracked video, and performing target detection on the to-be-tracked video to obtain a key frame image containing a tracking target; performing image recognitionon the key frame image to obtain an object area containing a tracking target, and performing key point extraction on the object area to obtain key point data of the tracking target; extracting a to-be-detected image of a next frame adjacent to the key frame, and performing feature extraction on the to-be-detected image to obtain a second feature map of the to-be-detected image; inputting the second feature map and the key point data into a prediction model as input parameters to obtain corresponding prediction key point data of each key point in the to-be-detected image; and determining the tracking target in the to-be-detected image according to the predicted key point data.

The invention discloses a three-dimensional reconstruction method and system in intelligent transportation. The three-dimensional reconstruction method comprises the steps of obtaining information of a detection scene, achieving extraction and dynamic tracking of target feature points in the detection scene, achieving feature point automatic completion and conducting three-dimensional reconstruction on targets through a distribution reconstruction algorithm. The three-dimensional reconstruction method comprises the following steps of S101, carrying out camera calibration, S102, synchronously obtaining original video images with scene depth information, S103, tracking feature points of the targets in a video scene, S104, selecting video key frames, S105, reconstructing the selected frames, S106, packaging subsets, and S107, obtaining a final three-dimensional model. According to the three-dimensional reconstruction method and system in intelligent transportation, an improved KLT tracking algorithm is adopted, a feature point model is optimized, and tracking efficiency is improved; the key frames are extracted to serve as the subsets, and the subsets are reconstructed and finally are merged, so that the problems that the obtained video frames are relatively short, and depth obtaining of image information is influenced by tracking losing of feature points in the scene, faults and the like are solved.

The invention discloses a solar automatic tracking system comprising hardware which has a smart structural design with single-axle scaly solar panels (1) and a universal joint bearing seat (5), and the solar automatic tracking system is suitable for a shaft support with multiple pillars, is mounted in complex hilly lands, has down-moved gravity of the support and flexible turning and enables the system to adopt a single-axis tracking system to establish a solar power station in bumpy hilly lands, thereby ensuring that the solar panels always obtain solar radiation energy as much as possible in the hilly lands, enhancing the tracking efficiency, effectively improving the anti-wind capability of the hardware, reducing the material breakage brought by windage resistance and strengthening the security and the adaptability. With a unique shadow elusion system processing function, the system prevents the solar panels on a stand from generating energy degradation because of being sheltered from mutual shadows and enables the solar panels to obtain the greatest energy output, thereby not only improving the solar electrical energy generation efficiency greatly, but also enhancing the adaptability of the solar tracking system and saving the limited resources by saving occupied space about 50 percent compared with the prior solar tracking system.

The invention discloses a method for tracking mixing features. Feature points of key frame images are extracted and saved by SIFT (scale-invariant feature transform) algorithm. A KLT (Kanade-Lucas-Tomasi feature tracker) algorithm thread tracks the feature points of the key frame images by KLT algorithm to obtain the feature points of current frame images, detects whether number of the feature points is sufficient or not for the next tracking after homography is successfully calculated, and notifies a SIFT algorithm thread when the feature points are insufficient. The SIFT algorithm thread extracts and matches the feature points according to the notice given by the KLT algorithm thread, and returns the matched feature points to the KLT algorithm thread. The KLT algorithm thread blends the received feature points returned by the SIFT algorithm thread into tracking feature points remained in the KLT algorithm thread for tracking. The invention further discloses a device for tracking mixing features. By the method and the device, stable tracking is achieved. The method and the device are applicable to camera tracking fields such as virtual studios and virtual sports.

The invention discloses a target real-time tracking method and device, a computer device and a storage medium. The target real-time tracking method comprises the following steps: acquiring original video data; selecting a reference image from the original video data and detecting an object to obtain at least one reference tracking object and a corresponding reference object feature vector; performing target detection on the current image to obtain at least one current tracking target and a corresponding current target feature vector; determining feature similarity of each benchmark tracking target based on the benchmark target feature vector and the current target feature vector; if the feature similarity is less than the preset similarity, determining the reference tracking target corresponding to the feature similarity to be a missing tracking target in the current image; and if the feature similarity is less than the preset similarity; if the reference tracking target is lost in theN consecutive frames after the current image, releasing the reference tracking target. The real-time target tracking method can judge and release the lost target, and improve the accuracy and efficiency of target tracking.

The invention discloses a method and device for recognizing vehicle information, and the method comprises the steps: recognizing identification information of a photographed vehicle according to a vehicle travel record image; judging whether the photographed vehicle is a vehicle breaking the law or not according to the identification information of the photographed vehicle; and recording the travel information of the photographed vehicle if the photographed vehicle is the vehicle breaking the law. The method provided by the invention can effectively recognize whether the photographed vehicle is the vehicle breaking the law or not. When the photographed vehicle is the vehicle breaking the law, the method can transmit the useful information, which comprises the license plate number of the photographed vehicle and the time and place of meeting with a user vehicle, to a law enforcement department, thereby enabling the law enforcement department to quickly track the vehicle breaking the law according to the clue provided by the user, and improving the tracking efficiency of the vehicle breaking the law.

The embodiment of the invention provides an object identifying and tracking method and device. The method comprises the steps that a current frame image to be identified is acquired in a video stream; an identified object in the current frame image is detected, and a detection box list is obtained; a superposition range of each first detection box and a corresponding second detection box stored in a preset object identification information table is determined according to each first detection box in the current frame image; and if any superposition range is greater than a first preset threshold value, it is determined that an object identifier corresponding to information of each first detection box is the same as an object identifier corresponding to information of the corresponding second detection box. Through the method, object identifiers of identified objects in the first detection boxes can be determined without the need for identifying images of the identified objects in the first detection boxes and the second detection boxes, time spent by a user waiting for an image identification result is saved, and the efficiency of identifying identified objects in all frame images in the video stream is improved.

The invention discloses an augmented reality tracking method based on a neural network. The augmented reality tracking method includes the steps that S1, a neural network structure is established; S2, motion data of a target object in an image sequence serve as training data so as to train the neural network, and weights of all layers in the neural network are adjusted; S3, the angular point features of a first image in a video are extracted; S4, through neural network prediction, the motion tendency of the target object is acquired; S5, the target object is tracked in the direction of the motion tendency of the target object and in the follow-up image sequence. According to the method, the motion tendency of the target object is predicted through the neural network, the search range and the number of iteration times in the calculation process are reduced, thus, the tracking calculation time is shortened, and the tracking efficiency is improved.

The invention discloses a network tracking system based on digital watermarking and the honeypot technology. The network tracking system comprises a trap system and an attack tracking system. The trap system is mainly composed of a honeypot system module and a digital watermarking system module. According to the network tracking system, tracking initiative is enhanced and various cost of tracking is reduced in comparison with existing network tracking systems, and the network tracking system has higher accuracy, effectiveness and operability in the aspects of realization and effect.

The invention provides a station interlocking logic processing method and device. The method includes the steps that small access virtualization processing is conducted on station access; after an access sequence table is obtained, if a progressive change happens to the access sequence table, interlocking processing is conducted on all access commands not sending out admission authorization in theaccess sequence table one by one; if a route change happens to the access sequence table, all access in a station is unlocked, a permission used for canceling access idleness and admission is sent out, and then interlocking processing is conducted on all the access commands in the access sequence table; after it is detected that a train sequentially occupies the cleared access, the permission used for canceling access idleness and admission is sent out to a train control system; whether small access occurs in following access or not is judged, and according to a judgment result, the small access is locked or unlocked again after being locked or unlocked; and a permission for small access idleness and admission is sent out to the train control system according to the small access locked and unlocked again. By the application of the method and device, train tracking efficiency can be improved.

The invention relates to a log tracking method and device, computer equipment and a storage medium. The method comprises the following steps of: receiving a log query request sent by a terminal, wherein the log query request carries one or more operation request identifiers; obtaining corresponding tracking identifiers according to the operation request identifiers; obtaining indexes correspondingto the tracking identifiers, and querying log messages corresponding to the tracking identifiers through the indexes; and returning the log messages to the terminal and displaying the log messages ina page of the terminal. By adoption of the method, the log tracking efficiency can be effectively improved.

The present disclosure provides a method and a device for target tracking. The method includes: obtaining a primary forecasting model and a verification model of a target, the primary forecasting model containing low-level features of the target and the verification model containing high-level features of the target; obtaining a current frame of a video image and determining a tracking region of interest (ROI) and a motion-confining region in the current frame based on a latest status of the target, wherein the tracking ROI moves in accordance to a movement of the target; forecasting a status of the target in the current frame in the tracking ROI based on the primary forecasting model; and determining a target image containing the target based on the status of the target in the current frame. The method further includes extracting high-level features of the target from the target image.

The invention relates to the technical field of information safety, particularly to a method and a system for auditing and distributing sensitive data based on an evolution strategy. The system of the invention comprises a risk evaluation module based on trust, an auditing and distributing module based on a strategy, a data leakage auditing module and a sensitive data management service module; the risk evaluation module calculates the trust level of the user behavior and investigates the intersection of a leakage set and an intersection of an acquired set of the user, so that the crime risk of the user is obtained; the distributing module determines a distribution policy under the guide of a crime factor and a judging sum formula according to user application and distribution records; and the auditing module records a distributing log, counts the information for analyzing the user behavior and the data leakage, and feeds back an auditing result to the risk evaluation module and the distributing module. The invention meets the requirements of the anti-leakage application of the sensitive data having high requirements for data completeness; the detection source is detected by the intersection of the acquired data set of the user and the leakage data set; and no watermark information needs to be imbedded, so that the invention meets the application requirements of the sensitive data having high requirements for the completeness and the privacy.

The invention discloses a human body tracking method based on a Gaussian mixture model in the image processing technical field. The invention firstly uses a linear model of a human body to establish a model to the human body, the head, the neck, the mass center and two feet of the human body are taken as tracking positions, then each tracking position of the human body is made a Kalman filtering tracking in a subsequent frame, wherein, two legs are tracked based on a Gaussian mixture model, the left foot adopts the Kalman filtering to track, and the motion state of the right foot is judged through the state of the left foot to simplify the tracking to the right foot. The invention forecasts the parameter of the component in the next frame through the Kalman filtering and uses the observed value to modify the predicted value, thereby assuring the accuracy of the component tracking. To use the Gaussian mixture model to build models for the tracked objects improves the tracking efficiency and can recognize the state of the motion of two legs.

The invention discloses a motion tracking method and a device. The method includes the following steps: A. conducting motion detection on a present frame to obtain all motion areas; B. as for a motiontarget to be tracked, allocating weight value to all pixel points of the motion target according to the principle that the smaller champer distance is, the smaller the weight value is, and accordingto the champer distance of all pixel points of the motion target of the prior frame; C. according to the principle that the smaller champer distance is, the smaller the weight value is, and accordingto the champer distance of all pixel points of all motion areas of the present frame, allocating weight value to all pixel points in the motion area; and D. according to the weight value allocated insteps B and C, searching a motion area with the color most similar to that of the motion target in all the motion areas of the present frame, wherein the motion area is rightly the tracking object ofthe motion target in the present frame. The method and the device improve tracking reliability.