Research on Object Tracking Algorithm Based on Sparse Representation
- 10.2991/icmmita-15.2015.285How to use a DOI?
- Visual Tracking; Sparse Representation; Classification.
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.
- © 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/).
Cite this article
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 -