A Target Tracking Method Based on Sparse Representation

A sparse representation and target tracking technology, applied in the field of target tracking, can solve problems such as difficult target tracking and achieve good robustness
CN104361609BActive Publication Date: 2017-12-01UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
UNIV OF ELECTRONICS SCI & TECH OF CHINA
Publication Date
2017-12-01

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Abstract

The invention relates to the target tracking technology and discloses a target tracking method based on sparse representation. According to the technical scheme, sparse learning is conducted on obstructions by means of the spatial continuity and prior information of the obstructions, the sparse coefficient is obtained by means of an updated sparse representing model on this basis, the reconstitution residual error is calculated according to the obtained sparse coefficient, real-time updating is conducted on a redundant dictionary with the minimum target of the reconstitution residual error as a tracking target, the position of the target at the next moment is predicted with the particle filter tracking method, an estimation target is obtained, and finally the obtained estimation target and the updated redundant dictionary are fed back to the sparse representing model to conduct repeated iteration. According to the method, the sparse learning idea is introduced to the particle filter tracking algorithm based on sparse representation, sparse learning of the obstructions and establishment of an obstruction model can be conducted under the condition that the obstructions are not sparse, and accurate tracking of the target can be conducted according to the updated sparse representation model.
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Description

technical field

[0001] The invention relates to target tracking technology, in particular to a sparse representation-based particle filter tracking method for occluded target tracking. Background technique

[0002] In the target tracking technology, the traditional target tracking method has the Mean-Shift tracking algorithm based on target pattern search and matching (see Comaniciu D, Ramesh V, Meer P. Kernel-Based Object Tacking. IEEE Trans on Pattern Analysis and Machine Intelligence, 2003, 25(5):564-577), classification-based Boosting target tracking algorithm (see] Avidan S.Ensemble Tracking.IEEE Trans on Pattern Analysis and Machine Intelligence, 2007, 29(2):261-271), based on Kalman filter Tracking algorithm (see Yim J, Jeong S, Gwon K, et al.Improvement of Kalman Filters forWLAN Based Indoor Tracking.Expert Systems with Applications, 2010, 37(1):426-433) and tracking algorithm based on particle filter ( See Wang Zhaowen, Yang Xiaokang, Xu Yi, et al. CamShift Guided ...

Claims

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