Target Tracking Algorithm Based on Improved Meanshift

Tian, 王田 Wang; Wei-ning, 刘伟宁 Liu; Guang-liang, 韩广良 Han; Chao, 杜超 Du; Lian, 刘恋 Liu

doi:10.3788/yjyxs20122703.0396

Cited by 5 publications

(1 citation statement)

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“…At present, the mainstream tracking algorithms mainly include Kalman filter tracking [25], particle filter tracking [26] and kernel tracking [27], The advantages and disadvantages of various methods are different. Meanshift algorithm [28][29][30] is the most commonly used kernel tracking method, because of its outstan ding real-time, robustness to interference and so on has been widely used. Different tracking methods have their own advantages, and the target tracking process requires high real-time performance of the algorithm, so this paper mainly studies the meanshift algorithm and its improved algorithm.…”

Section: Status Of Researchmentioning

confidence: 99%

An Anti-occlusion Video Target Tracking Method Based on Kalman Filter

Kexin¹

2019

JEEE

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The human visual system is the main component of the brain-based information processing system. It is the main way for humans to obtain external information. Therefore, the emerging science represented by computer vision came into being. Video-specific target tracking is a core issue in the field of computer vision research. It has been widely studied and concerned, and it has been widely used in many fields, such as video surveillance, intelligent navigation, medical diagnosis, augmented reality and virtual reality, etc. The specific moving target tracking algorithm and improved algorithm in the video are studied to some extent. Combining the meanshift algorithm with Kalman filtering can solve the occlusion problem of moving targets in complex scenes. This project intends to use Kalman filter and meanshift algorithm to detect and track the specified target in the video image sequence, and obtain the position, angle, scale, velocity, acceleration and dynamic trajectory of the target. Experiments show that this method has a good tracking effect on the target tracking in the video which is partially occluded during the motion.

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Section: Status Of Researchmentioning

confidence: 99%

An Anti-occlusion Video Target Tracking Method Based on Kalman Filter

Kexin¹

2019

JEEE

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A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching

Duan¹,

Ping²,

Chen³

et al. 2018

西北工业大学学报

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This paper proposes a target tracking algorithm based on mean shift and template matching. The algorithm is divided into three stages:prediction, template matching, target positioning, and template updating. In the prediction stage, combined with the target position obtained from the previous frame tracking, the target position is predicted using the mean shift method, and the template matching search gate is defined with the predicted position as the center and the corresponding size as the coverage area. At the template matching stage, using fast template matching algorithm, the target template and search gate are quickly matched from coarse to fine, and the matching degree between matching result and target template is calculated. If the matching degree is greater than the given threshold, the fast template matching will be performed and the result will be used as the tracking result of the current frame image. Otherwise, the target position predicted by the mean shift algorithm is used as the tracking results of the current frame image. Finally, the template updating process is controlled by the tracking results of the current frame to update the target template, and the stable tracking of the target is finally completed. At the same time, the algorithm improves the robust of tracking by combining the advantages of color and edge features to the insensitivity of rotation and deformation. The method has fast calculation speed and high accuracy, it can meet real-time requirements.

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Research of meanshift tracking algorithm based on feature matching estimation

Xingmeng

Chen

2017

2017 Chinese Automation Congress (CAC)

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Target Tracking Algorithm Based on Improved Meanshift

Cited by 5 publications

References 0 publications

An Anti-occlusion Video Target Tracking Method Based on Kalman Filter

An Anti-occlusion Video Target Tracking Method Based on Kalman Filter

A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching

Research of meanshift tracking algorithm based on feature matching estimation

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