An Improved TLD Visual Tracking and Detection Algorithm Based on Depth Image Information

DOI

10.2991/mse-15.2016.47How to use a DOI?

Keywords

visual tracking; tracking-learning-detection; depth information; blob detection

Abstract

Tracking-Learning-Detection(TLD) algorithm has the advantages of high speed, high accuracy of tracking rate and self-detection mechanism. However the sensitivity to illumination variation and background clutter leads to drift even miss for TLD algorithm under the complex environment. An improved TLD visual tracking algorithm based on depth information is proposed, which is improved from three aspects. The first is that a foreground extraction algorithm based on denoised depth data is adopted to extract the region of interest. Second, a sophisticated detection of blob approach is used to narrow down the searching area. And the third is that the non-maximal suppression strategies are applied to optimize the result. The experimental results show that the time complexity of proposed is decreased and the robustness is upgrade under challenging circumstances.

Copyright

© 2016, 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/).

Download article (PDF)

TY  - CONF
AU  - Jialiang Mao
AU  - Xiaorong Shen
PY  - 2016/03
DA  - 2016/03
TI  - An Improved TLD Visual Tracking and Detection Algorithm Based on Depth Image Information
BT  - Proceedings of the 2015 International Conference on Mechanical Science and Engineering
PB  - Atlantis Press
SP  - 274
EP  - 282
SN  - 2352-5401
UR  - https://doi.org/10.2991/mse-15.2016.47
DO  - 10.2991/mse-15.2016.47
ID  - Mao2016/03
ER  -