Nonlinear approach to shot boundary detection

Kien A. Hua; JungHwan Oh; Khanh Vu

doi:10.1117/12.410900

22 December 2000 Nonlinear approach to shot boundary detection

Kien A. Hua, JungHwan Oh, Khanh Vu

Proceedings Volume 4312, Multimedia Computing and Networking 2001; (2000) https://doi.org/10.1117/12.410900
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

Shot boundary detection (SBD) is the first fundamental step to managing video databases. It segments video data into the basic units for indexing and retrieval. Many automatic SBD techniques exist. They, however, are based on sequential search, and therefore too expensive for practical use. To address this problem, we explore a different direction to SBD in this paper. We investigate a non-linear approach in which most video frames do not need to be compared. This idea is fundamentally different from all existing methods. In fact, it is orthogonal to these schemes in the sense that it can be applied to substantially improve their performance. Our experiments show that this idea speeds up a conventional method based on color histograms up to 16 times while preserving the same accuracy. On the average, the improvement is five time according to our experiments on 26 videos of six different types.

Citation Download Citation

Kien A. Hua, JungHwan Oh, and Khanh Vu "Nonlinear approach to shot boundary detection", Proc. SPIE 4312, Multimedia Computing and Networking 2001, (22 December 2000); https://doi.org/10.1117/12.410900

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