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120 results about "Visual target tracking" patented technology

Visual target tracking method of full-convolution integral type and regression twin network structure

A visual target tracking method of a full convolution class and regression twin network structure comprises the following steps: (1) according to the position of a target in an image, cutting a targettemplate image and a search area image in an original training set, and forming a training data set by cut image pairs; (2) establishing a full convolution twin network to extract image features; (3)establishing a classification regression network; (4) in response to the fact that each pixel point on the image has a corresponding foreground score and a predicted bounding box, calculating the total score of each pixel point by combining the information of the foreground score and the information of the bounding box, wherein the pixel point with the highest total score is the center of the tracking target; and (5) training the full convolution twin network and the classification regression network by using the training data set to obtain the trained full convolution twin network and the classification regression network, calculating a score graph of a target in the to-be-tested image sequence by using the trained networks, and performing target positioning based on the score graph. According to the invention, the tracking precision and speed are improved.
Owner:ZHEJIANG UNIV OF TECH

Visual target tracking method based on self-adaptive subject sensitivity

The invention discloses a visual target tracking method based on self-adaptive subject sensitivity, and belongs to the technical field of computer vision. The visual target tracking method comprises an overall process, an offline part and an online part. The whole process includes: designing a target tracking process, and designing a network structure; adjusting the feature map of each stage of the network into an adaptive size to complete the end-to-end tracking process of the twin network; the offline part comprises six steps: generating a training sample library; carrying out forward tracking training; calculating a back propagation gradient; calculating a gradient loss item; generating a target template image mask; and training a network model and obtaining the model. The online part comprises three steps: carrying out model updating; carrying out online tracking; and positioning a target area. The model updating comprises forward tracking, back propagation gradient calculation, gradient loss item calculation and target template image mask generation; the online tracking comprises the steps of performing forward tracking to obtain a similarity matrix, calculating the confidencecoefficient of a current tracking result and returning to a target area. The method can better adapt to target robust tracking of appearance changes.
Owner:BEIJING UNIV OF TECH

Combined judging strategy-based visual target tracking method

The invention relates to a combined judging strategy-based visual target tracking method. The method comprises the following steps of: (1) aiming at a target size change problem, establishing a self-adaptive scale so as to automatically adjust the size of a tracking frame; (2) aiming at a problem that a position of a target cannot be continuously determined after the target is sheltered, predicting a current observed quantity by adoption of Kalman filtering, and after the target reappears, continuously tracking the target by using a KCF algorithm; and (3) aiming at a problem of tracking failure caused by rapid movement of the target. According to the method, a movement speed of the target is calculated through detecting a position movement distance of the target in adjacent frames, and a detection area size extension coefficient is self-adaptively adjusted, so that relatively high precision can be obtained under different environments, the robustness of the whole tracking system is effectively improved, a relatively high calculation speed is kept, and a high engineering practical value is provided.
Owner:BEIHANG UNIV

Visual target tracking method and system for unmanned aerial vehicle

The present invention is applicable to the technical field of unmanned aerial vehicles, and provides a visual target tracking method for an unmanned aerial vehicle. The method comprises the following steps: step A, conducting FAST angular point extraction for a first target region selected for tracking, generating a weighted FAST angular point histogram for the first target region, and calculating, according to the generated FAST angular point histogram, a FAST angular point feature similarity between the first target region and candidate target regions selected for tracking; step B, calculating a color feature similarity between the candidate target regions selected for tracking and the first target region, fusing the FAST angular point feature similarity and the color feature similarity, and using a candidate target region which has a highest similarity to the first target region according to the fusing result as a tracking result for the current target region. According to the present invention, the FAST angular point feature and the color feature are fused, thereby effectively using partial information and global information of the image, and thus reducing the impacts caused by a vehicle-mounted sensor to target state estimation.
Owner:深圳市易恬技术有限公司

Quad-rotor unmanned aerial vehicle visual target tracking method based on binocular camera

ActiveCN110222581AChoose Quickly and AccuratelyChoose to achieveTarget-seeking controlThree-dimensional object recognitionLoop controlGoal recognition
The invention discloses a quad-rotor unmanned aerial vehicle visual target tracking method based on a binocular camera. The method comprises the following steps of detecting a tracking target througha target recognition algorithm, finishing the position tracking and scale tracking of the target in pixel significance by using a visual tracking algorithm based on correlation filtering, and judgingwhether a repositioning program needs to be started or a long-term tracker needs to be updated according to a tracking effect; secondly, according to an image area selected by the tracking frame, calculating the relative distance between the quad-rotor unmanned aerial vehicle and the tracking target by using an LK optical flow method, and after coordinate conversion, realizing the global state estimation of the tracking target by using a Kalman filter; and finally, according to the estimated global position and speed state of the target, designing the state quantity of an outer loop control system of the unmanned aerial vehicle to realize the delay-free stable tracking of the tracked target by the unmanned aerial vehicle.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA

Smart visual holder system and realization method thereof

The invention relates to a smart visual holder system and a realization method thereof. The system comprises an image collection module which is used for collecting high-speed high-definition sequence images and sending the collected images to a holder master control module; a tri-axial stabilizing holder which is used for controlling a posture of the image collection module; the holder master control module which interacts with the image collection module, the tri-axial stabilizing holder and an image processing module and is used for carrying out video coding and storage on the images collected by the image collection module; and the image processing module which is used for carrying out format conversion on the images received by the holder master control module from the image collection module and processing the images, thereby finishing visual target tracking under moving target indication and a variable field of view, and feeding back a processing result to the holder master control module. The technical problem that an existing system is low in intelligentization degree and single in function is solved. Two intelligent visual functions of moving target indication and variable field of view target continuous tracking are integrated, thereby facilitating use.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI +1

Optimization method of visual target tracking method based on particle filtering and optical flow vector

The invention discloses an optimization method of a visual target tracking method based on particle filtering and optical flow vector, belonging to the technical field of image / video post-processing. The method comprises the following steps: performing the parallel computing of each huge computation algorithms involved in the visual target tracking method based on particle filtering and optical flow vector in multiple CPUs, running a thread on each CPU to process a part of line data, evenly distributing all the line data to each CPU; and sending an event report to a thread synchronization manager after completing the task of each thread, and starting all the threads by the thread synchronization manager, when all the threads complete the current task, to start the subsequent task event. By using the method of the invention, the efficiency of the visual target tracking method based on particle filtering and optical flow vector can be increased, and the requirement on the real-time of the tracking method can be satisfied.
Owner:CHINA DIGITAL VIDEO BEIJING

Systems and methods for visual target tracking

A method for controlling a movable object to track a target object may be provided. The method may comprise: determining a change in one or more features between a first image frame and a second imageframe, wherein the one or more features are associated with the target object, and wherein the first image frame and the second image frame are captured at different points in time; and adjusting a movement of the movable object based on the change in the one or more features between the first image frame and the second image frame.
Owner:SZ DJI TECH CO LTD

Real-time visual target tracking method based on light streams

The invention discloses a real-time visual target tracking method based on light streams. The method includes: screening feature points rich in textural features, and tracking the feature points between every two frames of images to obtain feature point matching relations; filtering the feature points with large matching errors through various filter algorithms such as normalized correlation coefficients, forward-reverse tracking errors and random consistency detection to retain most reliable feature points so as to obtain the target motion speed in images; using the target motion speed as observation quantity, and estimating through Kalman filtering to generate the target position. Compared with a tracking algorithm, the method has the advantages that the method is unaffected by light, the target can be stably tracked under the conditions that the target moves, a camera moves, the target is blocked for a short term and the like. The method is high in calculation efficiency, and the tracking algorithm is verified for the first time on an ARM platform.
Owner:BEIHANG UNIV

Adaptive sub-block screening-based multi-clue visual tracking method

The invention belongs to the visual tracking field and relates to an adaptive sub-block screening-based multi-clue visual tracking method. The method comprises the following steps that: (1) saliency detection is performed on a target region, uniform block division is used in combination, so that candidate sub-blocks can be obtained; (2) multi-scale sampling is performed on the candidate sub-blocks, sub-blocks with large frequency-domain response and the corresponding scales of the sub-blocks are determined, and a candidate sub-block set is updated; (3) motion estimation is performed on the sub-blocks in the candidate sub-block set, and the current location of a tracking target is determined through the multi-clue fusion of the sub-blocks; and (4) a Gaussian kernel corresponding to the location of each sub-block is updated through the current location of the target, and sub-blocks which do not satisfy requirements are re-initialized. According to the adaptive sub-block screening-based multi-clue visual tracking method of the invention adopted, the interference of background can be removed, the visual constraints of middle-level features and the priori constraints of high-level languages are fully utilized, so that the locating of the target is more accurate. The adaptive sub-block screening-based multi-clue visual tracking method has the advantages of simple steps and small computation amount, and is suitable for performing visual target tracking under a blocking condition.
Owner:HUAZHONG UNIV OF SCI & TECH

Local distance study and sequencing queue-based visual target tracking method

The invention discloses a local distance study and sequencing queue-based visual target tracking method, which comprises: step 1, selecting a target and the adjacent background of the target in a first frame image by using a target frame and a background frame, randomly sampling in each frame to obtain two small image sheet sets representing the target and the local background of the target; studying the local distance metric function of each target small image sheet and establishing a sequencing queue of the function, and calculating the purity of the sequencing queue and establishing a target model; step 2, randomly sampling a next frame image to obtain a new small image sheet set; calculating the distances among each small image sheet in the target model and all new small image sheets, and establishing a sequencing queue; and calculating confidence coefficients of the new small image sheets according to the positions of the new small image sheets in each sequencing queue and establishing a confidence graph; step 3, determining the position of the target in a new frame image by using the confidence graph; step 4, updating the target small image sheet set and a background small image sheet set; and step 5, updating the target model, the local distance metric function and the purity, and returning to the step 2.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI

Visual target tracking method and system

The invention relates to a visual target tracking method and system. The visual target tracking method comprises the steps of obtaining a plurality of historical target templates and historical position information of a current video sequence of a to-be-tracked target; determining a plurality of groups of target template images and search areas from the current video sequence of the to-be-trackedtarget according to each historical target template; predicting prediction position information of the target template image in the search area according to the target positioning model, each group oftarget template images and the search area; Based on an action network model, determining a target position prediction revenue value of the target template image according to the prediction positioninformation of the target template image and the historical position information; And comparing the target position prediction revenue values of the target template images, and determining the prediction position information of the target template image with the maximum target position prediction revenue value, thereby accurately determining the prediction position information of the current frameimage of the to-be-tracked target.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI

Visual target tracking method based on scale adaptation and occlusion detection

The invention relates to a visual target tracking method based on scale adaptation and occlusion detection. The method comprises the following steps of according to a target position and a size determined by a previous frame, cutting an image block in a current frame and extracting the convolution characteristics of different layers as sample characteristic graphs; in each layer of the characteristic graph, using a nuclear correlation filtering method to acquire a response graph, and then linearly superposing the different layers of response graphs to acquire a response general graph, whereina position corresponding to a maximum value is a the target position of a current frame; collecting different sizes of samples at the target position and adjusting to a same size, and acquiring a scale response via a scale filter, wherein a scale corresponding to a maximum value is the optimum scale of the current frame; calculating the peak value side lobe ratio of the response general graph anddetermining whether a target is occluded; when the target is occluded, using a space-time context model to re-determine the target position; and updating the model and preparing for the determinationof the target position and the size of the next frame. In the invention, the accuracy and the robustness of visual target tracking are increased.
Owner:DONGHUA UNIV

Neutrosophic similarity measurement-based scale-adaptive visual target tracking method

InactiveCN108492313AImprove efficiencySmall amount of calculation for smart measurementImage enhancementImage analysisCosine similarityMean-shift
The invention relates to a neutrosophic similarity measurement-based scale-adaptive visual target tracking method. The method comprises the following steps of: selecting a to-be-tracked target area inan initial frame and calculating a target feature histogram and an initial background histogram; carrying out truth, falsity and indeterminacy measurement aiming at target feature attributes and background feature similarity attributes; establishing a neutrosophic weight vector; introducing the neutrosophic weight vector into a mean shift strategy to determine a target area of a current frame; calculating corresponding truth, falsity and indeterminacy measuring values aiming at scale reducing and expanding and determining a scale updating strategy according to cosine similarity measurement; and updating a target background feature histogram. The method disclosed by the invention has the beneficial effects that an extremely efficient mean shift algorithm is adopted, the corresponding neutrosophic measurement calculating amount is small, the weight vector and scale estimating is low in complexity and high in efficiency and the requirements of real-time target tracking are met; and by utilizing a neutrosophic set theory, the tracking performance of a tracking algorithm coping with challenges of complex backgrounds and like is effectively improved through taking the change of trackedtarget features and the similarity of target / background features into account.
Owner:SHAOXING UNIVERSITY

Weak structure perception visual target tracking method capable of fusing with context detection

The invention discloses a weak structure perception visual target tracking method capable of fusing with context detection. During initialization, a weak structure relationship between a target and each component of surrounding environment is perceived to establish a model. Model maintenance corresponds to the target and two surrounding component sets, and a feature point and a feature descriptor are used for expressing the appearances of the components. In a tracking process, the component sets are combined with a movement model to generate a potential target center, then, the potential target center is clustered to reject noise to obtain an accurate target position, and a target size is updated. Under a weak structure tracking frame, a bottom-up way and a top-down way are introduced to carry out target context detection in order to enhance the prediction of a component position. Bottom-up detection provides consistent tracking information for each component through the estimation of the local movement of a pixel level. Top-down detection constructs a superpixel nuclear model to learn a difference between the target and a background on a level of individual, and guidance information is provided for target positioning and model update.
Owner:GUANGDONG UNIVERSITY OF FOREIGN STUDIES

A target tracking method based on a three-branch neural network

The invention discloses a target tracking method based on a three-branch neural network, and belongs to the technical field of computer vision. Visual target tracking belongs to video analysis and serves as an important branch in the field of computer vision, and the basic task of the visual target tracking is to predict the position, area and motion track of a target in a video sequence accordingto given position information of the target in an initial frame. The precision and speed of visual target tracking are low, and the visual target tracking is easily affected by shielding, backgroundconfusion, size change, severe appearance change, illumination change and the like. The invention provides a target tracking method based on a three-branch neural network. Compared with the traditional visual target tracking technology, the three-branch neural network is utilized to track the target, so that the target can be represented with high robustness, the obvious change of the appearance of the target can be handled, the background can be well distinguished, and meanwhile, the drifting of the algorithm can be effectively avoided. And the tracking speed is far higher than that of otheralgorithms.
Owner:HARBIN ENG UNIV

Image attention visual target tracking method

The invention discloses an image attention visual target tracking method. The method comprises the following steps: (1) cutting a selected target tracking data set; (2) constructing a fully convolutional twin neural network for extracting image features; (3) building an image attention module; (4) building a classification regression network; (5) calculating a surrounding frame and a foreground score corresponding to each pixel point on the feature response graph after the feature response graph passes through the classification regression network, further calculating a total score of each pixel point according to the corresponding surrounding frame and the foreground score, and taking the point with the highest score as the central point of the tracked target; and (6) training the model by using a training data set to obtain a trained network model, and performing target tracking and positioning on the to-be-tested model by using the network. According to the invention, the tracking precision and speed are improved.
Owner:ZHEJIANG UNIV OF TECH

An unmanned aerial vehicle visual target tracking method based on scale adaptive kernel correlation filtering

The invention discloses an unmanned aerial vehicle visual target tracking method based on scale self-adaptive kernel correlation filtering, which comprises the following steps of selecting a trackingtarget, calculating to obtain the color and gradient initial probability density of a first frame of the tracking target, and training a classifier and detecting the central position of the target byusing the kernel correlation filtering algorithm for the first frame of data; establishing a one-dimensional kernel correlation filter from the second frame to detect the change of the target scale, and calculating kernel correlation filtering by using a convolution theorem; constructing a similarity function by utilizing the current target feature and the initial feature, if the similarity is smaller than a set threshold value, considering that the target identification is inaccurate or the target is lost, entering global search, otherwise, representing that the target is identified and tracked, and obtaining target position information; and sending the position information of the tracking target to an unmanned aerial vehicle flight control system in real time to control the position of the unmanned aerial vehicle. According to the method, the problem of fixed tracking scale of a kernel correlation filtering algorithm is optimized, and the tracking precision of target characteristicsis effectively improved.
Owner:NANJING UNIV OF AERONAUTICS & ASTRONAUTICS

Real-time visual target tracking method based on twin convolutional network and long short-term memory network

The invention relates to a real-time visual target tracking method based on a twin convolutional network and a long short-term memory network, which comprises the following steps of: firstly, for a video sequence to be tracked, taking two continuous frames of images as inputs acquired by the network each time; carrying out feature extraction on two continuous frames of input images through a twinconvolutional network, obtaining appearance and semantic features of different levels after convolution operation, and combining depth features of high and low levels through full-connection cascading; transmitting the depth features to a long-term and short-term memory network containing two LSTM units for sequence modeling, performing activation screening on target features at different positions in the sequence by an LSTM forgetting gate, and outputting state information of a current target through an output gate; and finally, receiving a full connection layer output by the LSTM to output the predicted position coordinates of the target in the current frame, and updating the search area of the target in the next frame. The tracking speed is greatly improved while certain tracking stability and accuracy are guaranteed, and the tracking real-time performance is greatly improved.
Owner:NANJING UNIV OF POSTS & TELECOMM

Rotor operation flying robot target tracking method and system

The invention belongs to the technical field of visual target tracking, and discloses a rotor operation flying robot target tracking method and system, and the method comprises the steps: taking a Siamfc framework as the basis, introducing Resnet50 as a feature extraction network through offset learning, enabling the network to learn more semantic information, and coping with the appearance changeof a target; according to the tracking network, a target scale estimation module is newly added on the basis of a classification discriminator, an IOU of a target bounding box and a target real box can be predicted, the target bounding box is accurately predicted, iterative correction is carried out on the bounding box through reverse gradient, and thus the network can accurately predict the scale change of a target; output of different layers of the network is fused by utilizing Resnet50 multi-layer feature output and adopting a residual fusion strategy, so that the robustness of the algorithm is further improved, the network performance is improved, the discrimination capability of the network to a small target is guaranteed, and finally, accurate tracking of the target is realized.
Owner:HUNAN UNIV

Visual target tracking method based on credibility combination map model

The invention relates to the computer video processing technology, in particular to a visual target tracking method based on a credibility combination map model. The method comprises the following steps that (1) a training database is established; (2) features of the training database are extracted, and a two-dimensional disjunction unit classifier and a two-dimensional disjunction classifier are trained; (3) a credibility combination map of first-frame target objects is established; (4) features of a current-frame background frame are extracted; (5) a credibility graph is obtained; (6) a target is positioned, and a plurality of candidate windows are obtained; (7) a credibility combination map of the candidate windows is matched with the saved previous-frame credibility combination map, and optimal target location information is obtained; (8) an updating sample is obtained by means of combination map matching, and the classifiers, the credibility map model, the state of a tracker and the like are updated every five frames; (9) the step (4), the step (5), the step (6), the step (7) and the step (8) are repeated till a video is over. By means of the visual target tracking method based on the credibility combination map model, the problem of target drifting can be effectively restrained in the computer visual target tracking process, and therefore the stability of the tracker is improved.
Owner:北京交通大学长三角研究院

Visual target tracking method based on deep residual network characteristics

The invention discloses a visual target tracking method based on deep residual network characteristics. The visual target tracking method comprises the following steps: 1, selecting a characteristic layer of a deep residual network and calculating a weight; 2, extracting features of the first frame of actual input image; 3, constructing a response and initial position filter of the characteristicsof the first frame of actual input image; 4, performing scale sampling and fHOG feature extraction on the first frame of actual input image; 5, constructing an initial scale filter; 6, feature extraction of the second frame of actual input image; 7, position filtering; 8, weighting a position filtering response graph and positioning a target; 9, performing scale sampling and fHOG feature extraction on the target image; 10, performing scale filtering and scale estimation on the target feature vector; 11, updating the filter; And 12, inputting a next frame of actual input image, regarding the next frame of actual input image as a second frame of actual input image, and repeating the step 6. The method is high in tracking precision and success rate, adapts to target scale changes, and achieves the robust tracking of the target.
Owner:CHANGAN UNIV +1

Multi-thread visual target tracking method based on STC and block re-detection

The invention provides a multi-thread visual target tracking method based on STC and block re-detection, and the method comprises the following steps: S1, reading a first frame image, and determininga tracking target; S2, establishing a spatial context model for the first frame of image by adopting an STC algorithm; S3, performing blocking operation on a rectangular template area where a trackingtarget in the first frame image is located, and training an SVM classifier; s4, reading a next frame of image, learning from a previous frame of image to obtain a spatial context model, and calculating target neighborhood context priori; s5, updating the space-time context model of the current frame image; s6, obtaining a confidence map of the current frame image; s7, judging the shielded degreeof the tracking target in the current frame image according to the confidence probability; s8, selecting a corresponding processing strategy according to the judged shielding condition of the trackingtarget; and S9, circularly executing the steps S4-S8 until the current video or image sequence is completely processed. According to the invention, the target tracking reliability and the target tracking efficiency can be improved.
Owner:WUHAN UNIV

Single vision target tracking algorithm and system based on deep neural network

The invention relates to the field of visual target tracking, and discloses a single visual target tracking algorithm and system based on a deep neural network. The basic principle of the method is asfollows: a tracking target is specified by a first frame in an image sequence, target features and to-be-searched region features are extracted by adopting the same convolutional network in subsequent frames, convolution and foreground-background distinguishing networks are performed to obtain a target position, and the width and height of a target frame are obtained through regression, so that aregion frame where the target is located is obtained; and when the confidence value of the tracking target is lower than a certain degree, considering that problems such as target loss may occur, andperforming re-search by adopting a re-search strategy to ensure the tracking effect of the target. For targets of different sizes, the sizes of the targets are input into a size adjusting module, sothat the sample cutting size is dynamically adjusted according to the target sizes. Therefore, the template can adapt to targets with different sizes and different motion characteristics, and the tracking performance is improved.
Owner:北京理工大学重庆创新中心 +1

KCF tracking target loss detection method and system based on foreground detection

The embodiment of the invention relates to the technical field of visual target tracking, and discloses a KCF tracking target loss detection method and system based on foreground detection. The KCF tracking target loss detection method based on foreground detection comprises: extracting a foreground image by adopting a foreground detection algorithm; extracting a target detection frame by using aKCF tracking algorithm; obtaining a foreground region corresponding to the target detection frame, calculating the ratio of the target contour area in the foreground area to the total area of the foreground area; judging whether a KCF tracking target is lost or not by setting a ratio threshold. According to the KCF target tracking method and device, the problems that the KCF algorithm cannot be perceived after the target is lost and the KCF tracker takes the background information as the target to continue tracking are solved, and accurate judgment when the tracking target is shielded in a large area or leaves a lens is realized on the basis of not influencing the real-time performance of KCF target tracking.
Owner:四川航天神坤科技有限公司

Robust visual target tracking method suitable for long-range tracking

The invention discloses a robust visual target tracking method suitable for long-range tracking. The method includes: extracting positive and negative samples according to an initial frame image of avideo sequence and position information of a target in an initial frame, performing feature extraction on sample image blocks to obtain low-dimensional eigenvectors, using the linear support vector machine technique to initialize a target appearance model; performing logistic regression on the obtained support vector machine model, and estimating a target position for the target appearance model under a particle filtering framework; combining the median flow tracking algorithm and the current particle filtering algorithm to perform collaborative tracking, using the incremental reduction technique to update the appearance model online in the tracking process, and combining the original appearance model and new samples to update the appearance model online till the last frame is updated. Inthis way, the visual target tracking of the robust is achieved. The parallel complementation of the two-way tracking method with different mechanisms is achieved, and the problem of spatial redundancycaused by continuously generating new information in the tracking process can be solved.
Owner:NANJING UNIV OF SCI & TECH

Visual target tracking method and system oriented to image sequence

The invention discloses a visual target tracking method and a visual target tracking system oriented to an image sequence. The visual target tracking method comprises the following steps of training aconvolutional regression model for target tracking by use of a given initialized image and a to-be-tracked target rectangular frame; predicating the position of a target by use of the convolutional regression model obtained by training; further predicting the size of the target on the basis of a prediction result of the target position; and updating the convolutional regression model according tothe position and the size of the target obtained by tracking. According to the visual target tracking method and the visual target tracking system oriented to the image sequence, technologies such astraining of a target overall regression model, training of a target texture regression model, prediction of the target position, prediction of the target size, updating of a tracking model and the like are involved, the interference of various environmental factors in a tracking scene can be fully overcome to implement accurate prediction for the target position and size, and relatively higher commercial values and research significances are possessed.
Owner:SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES

Model training method and device, terminal and storage medium

The embodiment of the invention discloses a model training method and device, a terminal and a storage medium. The method comprises: acquiring a template image and a test image; calling the first object recognition model to process the characteristics of the tracking object in the template image to obtain a first reference response, and calling the second object recognition model to process the characteristics of the tracking object in the template image to obtain a first reference response; calling the first object recognition model to process the characteristics of the tracking object in thetest image to obtain a first test response, and calling the second object recognition model to process the characteristics of the tracking object in the test image to obtain a second test response; tracking the first test response to obtain a tracking response of the tracked object; and updating the first object recognition model based on the difference information between the first reference response and the second reference response, the difference information between the first test response and the second test response and the difference information between the tracking tag and the tracking response. According to the embodiment of the invention, the accuracy of visual target tracking can be improved.
Owner:TENCENT TECH (SHENZHEN) CO LTD

Moving target visual tracking method based on multi-source information fusion

The invention belongs to the technical field of computer vision, and provides a moving target visual tracking method based on multi-source information fusion. Aiming at a moving target visual tracking task in a scene with rapid movement and severe illumination, the invention firstly manufactures a moving target tracking data set based on an event camera, and meanwhile, provides a visual target tracking algorithm based on cross-domain attention to accurately track a visual target based on the data set. According to the invention, the respective advantages of the frame image and the event data can be utilized and combined; the frame image can provide rich texture information; and the event data can still provide clear object edge information in a challenging scene. By respectively setting the weights of the two kinds of domain information in different scenes, the advantages of the two kinds of sensors can be effectively fused, so that the target tracking problem under complex conditions is solved.
Owner:DALIAN UNIV OF TECH
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