Multi-module human motion analysis from a monocular video

Weilun Lao; Jungong Han; Peter H. N. de With

doi:10.1117/12.705945

29 January 2007 Multi-module human motion analysis from a monocular video

Weilun Lao, Jungong Han, Peter H. N. de With

Proceedings Volume 6506, Multimedia Content Access: Algorithms and Systems; 65060M (2007) https://doi.org/10.1117/12.705945
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States

Abstract

In this paper, we propose an effective framework for semantic analysis of human motion from a monocular video. As it is difficult to find a good motion description for humans, we focus on a reliable recognition of the motion type and estimate the body orientation involved in the video sequence. Our framework analyzes the body motion in three modules: a pre-processing module, matching module and semantic module. The proposed framework includes novel object-level processing algorithms, such as a local descriptor and a global descriptor to detect body parts and analyze the shape of the whole body as well. Both descriptors jointly contribute to the matching process by incorporating them into a new weighted linear combination for matching. We also introduce a simple cost function based on time-index di.erences to distinguish motion types and cycles in human motions. Our system can provide three different types of analysis results: (1) foreground person detection; (2) motion recognition in the sequence; (3) 3-D modeling of human motion based on generic human models. The proposed framework was evaluated and proved its effectiveness as it achieves the motion recognition and body-orientation classification at the accuracy of 95% and 98%, respectively.

Citation Download Citation

Weilun Lao, Jungong Han, and Peter H. N. de With "Multi-module human motion analysis from a monocular video", Proc. SPIE 6506, Multimedia Content Access: Algorithms and Systems, 65060M (29 January 2007); https://doi.org/10.1117/12.705945

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