Finding Pictures of Objects in Large Collections of Images

Forsyth, David A.; Leung, Thomas K.; Bregler, Chris; Carson, C.; Greenspan, H.; Fleck, Margaret M.

Permalink

https://hdl.handle.net/2142/25948 Copy

Description

Title

Finding Pictures of Objects in Large Collections of Images

Author(s)

• Forsyth, David A.
• Leung, Thomas K.
• Bregler, Chris
• Carson, C.
• Greenspan, H.
• Fleck, Margaret M.

Issue Date

1997

Keyword(s)

• Digital Libraries
• electronic information resources
• digital images
• image access
• image retrieval
• detection rules
• grouping rules
• image segmentation
• visual primatives

Date of Ingest

2011-08-17T17:07:54Z

Abstract

"""Retrieving images from very large collections using image content as a key is becoming an important problem. Users prefer to ask for pictures using notions of content that are strongly oriented to the presence of objects, which are quite abstractly defined. Computer programs that implement these queries automatically are desirable but are hard to build be-cause conventional object recognition techniques from computer vision cannot recognize very general objects in very general contexts. This paper describes an approach to object recognition structured around a sequence of increasingly specialized grouping activities that assemble coherent regions of image that can be shown to satisfy increasingly stringent constraints. The constraints that are satisfied provide a form of object classification in quite general contexts. This view of recognition is distinguished by far richer involvement of early visual primitives, including color and texture; the ability to deal with rather general objects in uncontrolled configurations and contexts; and a satisfactory notion of classification. These properties are illustrated with three case studies: one demonstrates the use of descriptions that fuse color and spatial properties; one shows how trees can be de-scribed by fusing texture and geometric properties; and one shows how this view of recognition yields a program that can tell, quite accurately, whether a picture contains naked people or not."""

Publisher

Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign

Series/Report Name or Number

Digital Image Access & Retrieval [papers presented at the 1996 Clinic on Library Applications of Data Processing, March 24-26, 1996 Urbana-Champaign]

ISSN

0069-4789

Type of Resource

text

Genre of Resource

Conference Paper / Presentation

Language

en

Permalink

http://hdl.handle.net/2142/25948

Owning Collections