Color-based classifier for region identification in video

Richard P. Schumeyer; Kenneth E. Barner

doi:10.1117/12.298328

9 January 1998 Color-based classifier for region identification in video

Richard P. Schumeyer, Kenneth E. Barner

Proceedings Volume 3309, Visual Communications and Image Processing '98; (1998) https://doi.org/10.1117/12.298328
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

Content based coding has been proposed by several authors and members of the MPEG-4 community as a solution to very low rate video coding. Using content coding, a video sequence is decomposed into objects that may be encoded independently. Such a scheme requires a fast and accurate segmentation algorithm to identify various objects in the scene. In this paper we propose, develop, and analyze a color-based segmentation algorithm. One application of interest is coding of sign language video sequences. The requirements for accurate perception of sign language differ from those of traditional head-and-shoulders videoconferencing sequences. We propose a content-based coding method in which perceptually important regions in an image are identified, and more resources are allocated to these regions. Since face, hands and arms are important components of sign language, regions are defined that encompass these features. The dynamic segmentation algorithm identifies flesh regions using statistical methods operating on image color distributions. A method for performing the segmentation in the perceptually linear LAB space using data captured in the YC_bC_r space is developed. Results of encoding sign language sequences using the proposed content- based methods illustrate the improved quality that can be achieved at the same bit rate when compared to a uniform algorithm.

Citation Download Citation

Richard P. Schumeyer and Kenneth E. Barner "Color-based classifier for region identification in video", Proc. SPIE 3309, Visual Communications and Image Processing '98, (9 January 1998); https://doi.org/10.1117/12.298328

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