Regular Articles

Accurate object tracking system by integrating texture and depth cues

[+] Author Affiliations
Ju-Chin Chen, Yu-Hang Lin

National Kaohsiung University of Applied Sciences, Department of Computer Science and Information Engineering, No. 415, Jiangong Road, Sanmin District, Kaohsiung 807, Taiwan

J. Electron. Imaging. 25(2), 023003 (Mar 11, 2016). doi:10.1117/1.JEI.25.2.023003
History: Received June 4, 2015; Accepted February 12, 2016
Text Size: A A A

Abstract.  A robust object tracking system that is invariant to object appearance variations and background clutter is proposed. Multiple instance learning with a boosting algorithm is applied to select discriminant texture information between the object and background data. Additionally, depth information, which is important to distinguish the object from a complicated background, is integrated. We propose two depth-based models that can compensate texture information to cope with both appearance variants and background clutter. Moreover, in order to reduce the risk of drifting problem increased for the textureless depth templates, an update mechanism is proposed to select more precise tracking results to avoid incorrect model updates. In the experiments, the robustness of the proposed system is evaluated and quantitative results are provided for performance analysis. Experimental results show that the proposed system can provide the best success rate and has more accurate tracking results than other well-known algorithms.

© 2016 SPIE and IS&T

Citation

Ju-Chin Chen and Yu-Hang Lin
"Accurate object tracking system by integrating texture and depth cues", J. Electron. Imaging. 25(2), 023003 (Mar 11, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.2.023003


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.