Efficient subwindow search: A branch and bound framework for object localization

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 31, Issue 12, 2009, Pages 2129-2142

  Lampert, Christoph H ^a   Blaschko, Matthew B ^b   Hofmann, Thomas ^c  

^a MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

^b UNIVERSITY OF OXFORD   (United Kingdom)

^c GOOGLE   (Switzerland)

Author keywords

Branch and bound; Global optimization; Object localization; Sliding window

Indexed keywords

BINARY CLASSIFICATION; BRANCH AND BOUND; BRANCH AND BOUND SCHEMES; BRANCH AND BOUNDS; COMPUTATIONAL COSTS; DATA SETS; LARGE CLASS; LOCALIZATION PERFORMANCE; NEAREST NEIGHBOR CLASSIFIERS; OBJECT DETECTION; OBJECT LOCALIZATION; OBJECT LOCATION; OBJECT RECOGNITION SYSTEMS; OPTIMAL SOLUTIONS; QUALITY FUNCTION; SIMILARITY FUNCTIONS; SLIDING WINDOW; SUBIMAGES; SUBLINEAR TIME;

CLASSIFIERS; GLOBAL OPTIMIZATION; IMAGE RETRIEVAL; LEARNING SYSTEMS; LINEAR PROGRAMMING; OPTIMIZATION; SET THEORY; VOLATILE ORGANIC COMPOUNDS; WINDOWS;

OBJECT RECOGNITION;

EID: 70350621774     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2009.144     Document Type: Conference Paper

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