Behavior analysis of video object in complicated background

Wenting Zhao; Shigang Wang; Chao Liang; Wei Wu; Yang Lu

doi:10.1117/12.2246200

31 October 2016 Behavior analysis of video object in complicated background

Wenting Zhao, Shigang Wang, Chao Liang, Wei Wu, Yang Lu

Proceedings Volume 10020, Optoelectronic Imaging and Multimedia Technology IV; 100200H (2016) https://doi.org/10.1117/12.2246200
Event: SPIE/COS Photonics Asia, 2016, Beijing, China

Abstract

This paper aims to achieve robust behavior recognition of video object in complicated background. Features of the video object are described and modeled according to the depth information of three-dimensional video. Multi-dimensional eigen vector are constructed and used to process high-dimensional data. Stable object tracing in complex scenes can be achieved with multi-feature based behavior analysis, so as to obtain the motion trail. Subsequently, effective behavior recognition of video object is obtained according to the decision criteria. What’s more, the real-time of algorithms and accuracy of analysis are both improved greatly. The theory and method on the behavior analysis of video object in reality scenes put forward by this project have broad application prospect and important practical significance in the security, terrorism, military and many other fields.

Citation Download Citation

Wenting Zhao, Shigang Wang, Chao Liang, Wei Wu, and Yang Lu "Behavior analysis of video object in complicated background", Proc. SPIE 10020, Optoelectronic Imaging and Multimedia Technology IV, 100200H (31 October 2016); https://doi.org/10.1117/12.2246200

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available