Improved Spatio-Temporal Context Target Tracking Algorithm

DOI

10.2991/emim-17.2017.40How to use a DOI?

Keywords

Spatio-temporal context; SURF feature point; Target tracking; Obscure

Abstract

Visual tracking is one of the hot topics in the field of computer science. However, the effective use of context information can improve the robustness of video tracking due to factors such as illumination and rotation. The traditional spatio-temporal context algorithm does not detect the validity of the tracking result, so when the target is obscured for a long time, the tracking target is easily updated wrongly. Based on SURF feature point detection, an improved spatio-temporal context tracking algorithm is proposed. Using the SURF algorithm to extract the feature points from the initial model of the target as the evaluation criteria, the tracking target is evaluated and the target can be updated according to the standard when the target is blocked for a long time. Experiments show that the proposed algorithm can accurately update the target model when the target is obscured for a long time, and achieves reliable tracking.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuanhang Shi
AU  - Junwei Zang
AU  - Yuhuai Liu
PY  - 2017/04
DA  - 2017/04
TI  - Improved Spatio-Temporal Context Target Tracking Algorithm
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 185
EP  - 189
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.40
DO  - 10.2991/emim-17.2017.40
ID  - Shi2017/04
ER  -