PBIR: Perception-Based Image Retrieval-A system that can quickly capture subjective image query concepts

Proceedings of the ACM International Multimedia Conference and Exhibition

Volumn , Issue IV, 2001, Pages 611-614

  Chang, E ^a   Cheng, K T ^a   Lai, W C ^a   Wu, C T ^a  

^a University of California   (United States)

Author keywords

Active learning; Image retrieval; Query concept; Relevance feedback; Support vector machines

Indexed keywords

DATABASE SYSTEMS; FEATURE EXTRACTION; LEARNING ALGORITHMS; SEARCH ENGINES;

IMAGE QUERY; PERCEPTION-BASED IMAGE RETRIEVAL; SUPPORT VECTOR MACHINES;

IMAGE UNDERSTANDING;

EID: 0034787022     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Support vector machines for high-dimensional indexing
2. Mega - the maximizing expected generalization algorithm for learning complex query concepts (extended version)
3. Towards perception-based image retrieval
4. Learning image query concepts via intelligent sampling
5. Clustering for approximate similarity queries in high-dimensional spaces
6. Query refinement for multimedia similarity retrieval in mars
7. Support vector machine active learning for image retrieval
8. Falcon: Feedback adaptive loop for content-based retrieval