Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 35, Issue 12, 2013, Pages 2916-2929

  Gong, Yunchao ^a   Lazebnik, Svetlana ^b   Gordo, Albert ^c   Perronnin, Florent ^d  

^a University of North Carolina   (United States)

^b University of Illinois at Urbana Champaign   (United States)

^c UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

^d XEROX RESEARCH CENTRE EUROPE   (France)

Author keywords

binary codes; hashing; Large scale image search; quantization

Indexed keywords

ALTERNATING MINIMIZATION ALGORITHMS; CANONICAL CORRELATION ANALYSIS; HASHING; IMAGE SEARCH; NONLINEAR KERNEL MAPPING; ORTHOGONAL PROCRUSTES PROBLEM; QUANTIZATION; STATE-OF-THE-ART METHODS;

ALGORITHMS; BINARY CODES; IMAGE RETRIEVAL; METADATA;

ITERATIVE METHODS;

EID: 84887601251     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.193     Document Type: Article

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