8results about How to "Improve target tracking accuracy" patented technology

The application discloses a target tracking method and device under infrared active jamming based on probability data association, constructs a model set, determines target and infrared active jamming motion mode according to the model set, simulates an actual combat simulation scene; establishes a coalesced object measurement model and an infrared sensor error adaptive measurement model; estimates the actual size of the coalesced object, and pre-processes measurement information of the coalesced object measurement model and the infrared sensor error adaptive measurement model; data associates a plurality of measurement information, obtains a probability of measurement and track association; processes target motion model and the coalesced object measurement model and the infrared sensor error adaptive measurement model to predict target motion state, updates target motion state prediction; and obtains target state estimation and estimation error covariance. The application solves the problem of no accurate target measurement and measurement quality uncertainty when the target and the infrared active jamming coalesce, and improves the measurement accuracy.

The invention provides an airborne meteorological radar adaptive clutter suppression method, and belongs to the technical field of airborne meteorological radars, and the method specifically comprises the steps: calculating a reference angle iAngT between each distance unit and an airplane; calculating a first radar echo angle iAngR of each distance unit; calculating the error of the radar echo angle of each distance unit, and removing the error to obtain a corrected second radar echo angle; and performing ground clutter suppression on the radar data of the current antenna row, comparing the second radar echo angle of each distance unit with the reference angle, when the angle difference between the second radar echo angle and the reference angle is smaller than a preset value, considering that the current radar echo is a ground echo, and deducting the current radar echo to complete ground clutter suppression. Through the processing scheme provided by the invention, more accurate ground clutter suppression can be realized, the detection capability of low-altitude weather is improved, and the detection performance of the weather radar is effectively improved.

The application discloses a target tracking method and device and a computer readable storage medium, and the vehicle target detection model is used to obtain a vehicle target detection result; a single target tracker is used to perform motion prediction on a continuously updated target track and a target track which is not successfully associated with any detection of a current frame; an intersection-over-union based data association model is used to calculate the intersection-over-union between the prediction result and all current detections, and data association is performed based on the intersection-over-union; feature extraction and feature matching are performed on the lost target in the unassociated track and the unassociated detection, a re-identification matrix is constructed, then the detections with a similarity greater than a preset threshold value in the re-identification matrix are assigned to the corresponding track, and the state of the assigned track is updated. Through the implementation of the application, the temporarily lost vehicle target is continuously state estimated, and the lost target is supported to be re-identified, the target tracking precision is improved, in addition, the tracking structure is simple, and the real-time requirement of tracking can be effectively met.

This invention discloses a new media content acquisition system based on image data processing, belonging to the field of content acquisition technology. It includes a dynamic feature extraction module, a cross-frame feature bridging module, a dynamic re-identification mapping module, an illumination adaptive normalization module, and a multi-subject temporal fusion module. The dynamic feature extraction module acquires a continuous sequence of image frames, performs spatial and temporal feature extraction on each frame, and binds the extracted spatial and temporal features according to frame order to generate a dynamic feature sequence with a time index. This invention maintains feature continuity before and after occlusion through dynamic feature sequences and cross-frame bridging, achieving stable identity association and improving target tracking accuracy and acquisition stability. Furthermore, it achieves illumination adaptation and semantic consistency through dynamic re-identification and temporal fusion, ensuring the accuracy and reliability of content acquisition in multi-subject environments.

The invention discloses a multi-template collaborative preferential matching target tracking method, which comprises the following steps of: based on known target identification information, detecting a plurality of feature points in an area around a target, respectively establishing a feature point template and a target template, and simultaneously establishing a relative position relationship between the plurality of feature points and the target; respectively matching the feature point template established by the current frame image and the template of the target with the original image to be matched and the reduced image to be matched, preferentially selecting the matched feature point according to the matching coefficient, and obtaining the target feature point based on the fact that the relative position relationship between the feature point and the target in the actual scene is kept unchanged. The target position can be indirectly obtained through calculation according to the matched feature points; and then, according to a template matching coefficient of the target, allocating different weights to a target position obtained based on feature point matching calculation and a target position obtained based on template matching of the target, and finally obtaining a tracking position of the target and restoring the tracking position to an original image. According to the invention, the matching precision is improved.

The application provides a target tracking method, an electronic device, a storage medium and a program product, and relates to the technical field of target tracking. The method comprises the following steps: acquiring a video frame sequence, at least part of images in the video frame sequence comprising a target to be tracked; performing feature extraction on a current frame image by using a search network to obtain search features of the current frame image, the search features representing a position of the target to be tracked in the current frame image, and the search network being a convolutional neural network; performing convolution on the search features based on current template features corresponding to the current frame image to obtain a feature response map, the current template features representing a predicted target position of the target to be tracked in the current frame image, and the feature extraction network used for extracting the current template features and the search network being different neural networks; and inputting the feature response map into a regression network to obtain a tracking result, the tracking result comprising position information of the target to be tracked in the current frame image. The application can realize long-term and stable tracking of a target.

The invention provides a distributed target fusion tracking method and device based on space-time registration, and relates to the technical field of sensors. The distributed target fusion tracking method based on space-time registration comprises the following steps: selecting a mean value of a Gaussian component with the maximum weight from a plurality of Gaussian components of a posterior probability density expression of a space-time registration parameter as an estimated value of the space-time registration parameter; aligning the second posterior probability density with the first posterior probability density in time and space according to an estimated value of a space-time registration parameter by using a space-time registration formula of a uniform-speed motion model to obtain a calibrated second posterior probability density; and based on a generalized covariance cross fusion criterion, fusing the first posterior probability density and the calibrated second posterior probability density to obtain a target existence probability and a target space density of the tracking target. According to the invention, registration of multi-node sensor data can be realized with high precision and high reliability.

The invention discloses a multi-target tracking method based on a shielding state and a related device thereof, and the method comprises the steps: carrying out the target detection of a to-be-detected image collected by a camera, and recognizing the shielding state of each target according to the position of a detection frame of each target; the shielding state comprises light shielding, medium shielding and heavy shielding; carrying out ReID similarity-based matching on the detection frame of the lightly shielded target and the historical ReID vector set of the confirmed track; performing IoU-based matching on the detection frames of the medium-shielding and heavy-shielding targets and the unmatched confirmed tracks; performing IoU-based matching on the unconfirmed track and all the unmatched detection frames; and track updating is carried out after all matching is completed. Different matching methods are selected according to the shielding state of the target, stable tracking of the target in the shielding state is achieved, the target tracking accuracy in the shielding state is improved, and the technical problem that in the prior art, detection errors are large only when the target is shielded is solved.