Automatic video object segmentation and shadow detection for surveillance applications

Hao Yang; Like Zhang; Heng-Ming Tai; Chia-Jiu Wang

doi:10.1117/12.557448

2 November 2004 Automatic video object segmentation and shadow detection for surveillance applications

Hao Yang, Like Zhang, Heng-Ming Tai, Chia-Jiu Wang

Proceedings Volume 5558, Applications of Digital Image Processing XXVII; (2004) https://doi.org/10.1117/12.557448
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

This paper presents an object-based adaptive background update algorithm that is suitable for video surveillance in the dynamically changing environment. The background model is updated using information from not only the pixel change but also the currently detected object. The proposed method is able to deal with such problems as ghost and uncovered background. In addition, a shadow detection scheme is proposed to eliminate the shadow effect. Experimental results for three video sequences with different background situations are given to demonstrate the effectiveness of the proposed algorithm.

Citation Download Citation

Hao Yang, Like Zhang, Heng-Ming Tai, and Chia-Jiu Wang "Automatic video object segmentation and shadow detection for surveillance applications", Proc. SPIE 5558, Applications of Digital Image Processing XXVII, (2 November 2004); https://doi.org/10.1117/12.557448

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