Object Tracking Method Based on Superpixel and Local Sparse Representation

Authors

Huixian Yang, Physics and Optoelectronic Engineering College, Xiangtan University, Xiangtan 411105, China;
Liu Zhao, Physics and Optoelectronic Engineering College, Xiangtan University, Xiangtan 411105, China;
Liu Yang, Physics and Optoelectronic Engineering College, Xiangtan University, Xiangtan 411105, China;
Liu Fan, Physics and Optoelectronic Engineering College, Xiangtan University, Xiangtan 411105, China;
Dilong He, Physics and Optoelectronic Engineering College, Xiangtan University, Xiangtan 411105, China;

Abstract

Abstract: Due to the appearance changing of target object in object tracking, a tracking algorithm was proposed based on superpixel and local sparse representation (SPS). In training process, a discriminative appearance model was constructed by clustering the segmented train images; sparsity-based histogram of target object was calculated to construct generative appearance model. In tracking, superpixel-based confidence map was obtained, and the confidence values of candidates was sampled and calculated; the similarity between sparsity-based histogram of candidates and target template was computed by using local patches. Then motion model and observation model of candidates according to the confidence values and similarity of candidates were computed, which obtained maximum a posterior estimate of the samples and determined the track result. Furthermore, online updating of the two appearance model was kept independently. The experimental results and evaluations demonstrate that application of SPS algorithm can obtain accurate and robust track result with the appearance variation of target object.

Recommended Citation

Yang, Huixian; Zhao, Liu; Yang, Liu; Fan, Liu; and He, Dilong (2020) "Object Tracking Method Based on Superpixel and Local Sparse Representation," Journal of System Simulation: Vol. 28: Iss. 5, Article 4.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss5/4

First Page

1017

Revised Date

2015-05-03

DOI Link

https://doi.org/

Last Page

1030

CLC

TP391.9

Recommended Citation

Yang Huixian, Liu Zhao, Liu Yang, Liu Fan, He Dilong. Object Tracking Method Based on Superpixel and Local Sparse Representation[J]. Journal of System Simulation, 2016, 28(5): 1017-1030.