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Volumn 1, Issue , 2006, Pages 634-639

Semantics-biased rapid retrieval for video databases

Author keywords

Cluster; Index; Semantics; Video retrieval

Indexed keywords

APPROXIMATE NEAREST NEIGHBOR; APPROXIMATE SEARCHING; CLOSE-IN; CLUSTER; CLUSTER-BASED; CLUSTERING TECHNIQUES; CONTENT-BASED VIDEO RETRIEVAL; DATA SETS; FEATURE VECTORS; GAUSSIAN MIXTURE MODEL; HIGH-DIMENSIONAL INDEX; INDEX; NEAREST NEIGHBOR SEARCH; SECOND PHASE; SEMANTIC CLASS; SEQUENTIAL SEARCH; VIDEO DATABASE; VIDEO RETRIEVAL; VISUAL FEATURE;

EID: 78650063896     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/COGINF.2006.365559     Document Type: Conference Paper
Times cited : (1)

References (10)
  • 1
    • 17944378423 scopus 로고    scopus 로고
    • Dimensionality reduction for similarity searching in dynamic databases
    • K. V. R. Kanth, D. Agrawal, and A. Singh, "Dimensionality reduction for similarity searching in dynamic databases," Proc. ACM SIGMOD ICMD, pp. 166-176, 1998
    • (1998) Proc. ACM SIGMOD ICMD , pp. 166-176
    • Kanth, K.V.R.1    Agrawal, D.2    Singh, A.3
  • 2
    • 0012951952 scopus 로고    scopus 로고
    • A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces
    • R. Weber, H. Schek and S. Blott. "A Quantitative Analysis and Performance Study for Similarity-Search Methods in High-Dimensional Spaces," Proceeding of ACM VLDB '98, pp. 194-205, 1998
    • (1998) Proceeding of ACM VLDB '98 , pp. 194-205
    • Weber, R.1    Schek, H.2    Blott, S.3
  • 8
    • 1342281468 scopus 로고    scopus 로고
    • Addressing the problems of Bayesian network classification of video using high-dimensional features
    • February
    • A. Mittal, L.F. Cheong. "Addressing the problems of Bayesian Network Classification of Video Using High-Dimensional Features," IEEE Trans. On Knowledge and Data Engineering, vol. 16(2), pp.230-244, February, 2004
    • (2004) IEEE Trans. on Knowledge and Data Engineering , vol.16 , Issue.2 , pp. 230-244
    • Mittal, A.1    Cheong, L.F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.