OVID: toward object-based video retrieval

Barbara V. Levienaise-Obadia; William J. Christmas; Josef Kittler; Kieron Messer; Yusseri Yusoff

doi:10.1117/12.373586

23 December 1999 OVID: toward object-based video retrieval

Barbara V. Levienaise-Obadia, William J. Christmas, Josef Kittler, Kieron Messer, Yusseri Yusoff

Proceedings Volume 3972, Storage and Retrieval for Media Databases 2000; (1999) https://doi.org/10.1117/12.373586
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

The current trend in content-based retrieval is the development of object-based systems. Such systems enable users to make higher level queries which are more intuitive to them than queries based on visual primitives. In this paper, we present OVID, our Object-based VIDeo retrieval system. It currently consists of a video parsing module, an annotation module, a user interface and a search mechanism. A combined multiple expert approach is at the heart of the video parsing routine for an improved performance. The annotation module extracts color and texture-based region information which will be used by the neural-network-based search routine at query tie. The iconic query paradigm on which the system is based provides users with a flexible means to define object-based queries.

Citation Download Citation

Barbara V. Levienaise-Obadia, William J. Christmas, Josef Kittler, Kieron Messer, and Yusseri Yusoff "OVID: toward object-based video retrieval", Proc. SPIE 3972, Storage and Retrieval for Media Databases 2000, (23 December 1999); https://doi.org/10.1117/12.373586

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