Research on Object Tracking Algorithm Based on Sparse Representation

DOI

10.2991/icmmita-15.2015.285How to use a DOI?

Keywords

Visual Tracking; Sparse Representation; Classification.

Abstract

Visual tracking has been an active research topic which has a wide application in many computer vision tasks such as intelligence surveillance, vehicle navigation, human computer interaction, and so on. Introducing the background into the template set as the negative sample, the representative ones combine with positive samples as to build a new template set which is used to classify the sampling particles. The classification method filters out many samples which are largely dissimilar to the target, avoids the following computationally expensive cost of matching. Experiment shows that it cut down the redundant calculations.

Copyright

© 2015, 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  - Jianliang Meng
AU  - Rui Ni
AU  - Ye Wang
AU  - Peng Zhao
PY  - 2015/11
DA  - 2015/11
TI  - Research on Object Tracking Algorithm Based on Sparse Representation
BT  - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 1545
EP  - 1548
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-15.2015.285
DO  - 10.2991/icmmita-15.2015.285
ID  - Meng2015/11
ER  -