Finding objects in image databases by grouping

Retrieving images from very large collections, using image content as a key, is becoming an important problem. Finding objects in image databases is a big challenge in the field. The paper describes our approach to object recognition, which is distinguished by: a rich involvement of early visual pri...

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Bibliographic Details
Main Authors: Malik, J., Forsyth, D.A., Fleck, M.M., Greenspan, H., Leung, T., Carson, C., Belongie, S., Bregler, C.
Format: Conference Proceeding
Language:English
Subjects:
Computer science
Content based retrieval
Data mining
Histograms
Image databases
Image retrieval
Layout
Object recognition
Spatial databases
Tiles
Online Access:Request full text
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Summary:Retrieving images from very large collections, using image content as a key, is becoming an important problem. Finding objects in image databases is a big challenge in the field. The paper describes our approach to object recognition, which is distinguished by: a rich involvement of early visual primitives, including color and texture; hierarchical grouping and learning strategies in the classification process; the ability to deal with rather general objects in uncontrolled configurations and contexts. We illustrate these properties with three case studies: one demonstrating the use of color and texture descriptors; one learning scenery concepts using grouped features; and one demonstrating a possible application domain in detecting naked people in a scene.
DOI:10.1109/ICIP.1996.561012