Towards adaptive ontology-based image retrieval

17th GI-Workshop on the Foundations of Databases

Volumn , Issue , 2005, Pages 148-152

  Vompras, Johanna ^a  

^a HEINRICH HEINE UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COGNITIVE PROCESS; CONTENT-BASED IMAGE RETRIEVAL SYSTEM; DISCRIMINATIVE FEATURES; HIGH LEVEL KNOWLEDGE; HUMAN PERCEPTION; IMAGE DATA; IMAGE REPOSITORY; LARGE IMAGE DATABASE; ONTOLOGY-BASED; RELEVANCE FEEDBACK; RETRIEVAL PROCESS; SEMANTIC CONCEPT; SEMANTIC CONTENT; SEMANTIC GAP; SPATIAL CONTEXT; TEXT RETRIEVAL; VISUAL FEATURE;

CONTENT BASED RETRIEVAL; DATABASE SYSTEMS; FEATURE EXTRACTION; SEMANTICS;

DATA REDUCTION;

EID: 33750551027     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. G. Salton and M. McGill. Introduction to modern Information Retrieval. New York.
2. T. Huang, Y. Rui, M. Ortega, and S. Mehrotra. Relevance feedback: A power tool for interactive content-based image retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 1998.
3. J. Torres, A. Parkes, and L. Corte-Real. Region-based relevance feedback in concept-based image retrieval. Proc. of the 5th International Workshop on Image Analysis for Multimedia Interactive Services, Lisboa, Portugal., 2004.
4. A. B. Benitez and J.R. Smith. New frontiers for intelligent content-based retrieval. Proc. SPIE Vol. 4315, Storage and Retrieval for Media Databases, 141-152, 2000.
5. X. He, O. King, W.-Y. Ma, M. Li, and H.-J. Zhang. Learning a semantic space from user's relevance feedback for image retrieval. IEEE Transactions on Circuits and Systems for Video Technology, Vol. 13, 39-48., 2003.
6. G. B. Newby. Cognitive space and information space. Journal of the American Society of Information Science and Technology. 52, 1026-1048, 2001.