Adaptive object tracking based on an effective appearance filter

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 29, Issue 9, 2007, Pages 1661-1667

  Wang, Hanzi ^a   Suter, David ^b   Schindler, Konrad ^b   Shen, Chunhua ^c  

^a Johns Hopkins University   (United States)

^b MONASH UNIVERSITY   (Australia)

^c CSIRO   (Australia)

Author keywords

Appearance model; Color histogram; Mixture of Gaussians; Occlusion; Particle filters; Similarity measure; Visual tracking

Indexed keywords

COMPUTATIONAL METHODS; GAUSSIAN DISTRIBUTION; MATHEMATICAL MODELS; OBJECT RECOGNITION;

ADAPTIVE OBJECT TRACKING; COLOR HISTOGRAM; PARTICLE FILTERS; SIMILIARITY MEASURE; VISUAL TRACKING;

COLOR IMAGE PROCESSING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COLOR; COLORIMETRY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; METHODOLOGY; MOTION; NORMAL DISTRIBUTION; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COLOR; COLORIMETRY; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, STATISTICAL; MOTION; NORMAL DISTRIBUTION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 34548133657     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2007.1112     Document Type: Article

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