A mixed generative-discriminative framework for pedestrian classification

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Volumn , Issue , 2008, Pages

  Enzweiler, Markus ^a   Gavrila, Dariu M ^b,c  

^a UNIVERSITY OF HEIDELBERG   (Germany)

^b DAIMLER AG   (Germany)

^c UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; FEATURE EXTRACTION; IMAGE PROCESSING; NEURAL NETWORKS; PATTERN RECOGNITION; SUPPORT VECTOR MACHINES;

ACTIVE LEARNING; CLASSIFICATION PERFORMANCE; DISCRIMINATIVE APPROACH; GENERATIVE MODELING; HAAR WAVELETS; LARGE-SCALE EXPERIMENTS; PEDESTRIAN CLASSIFICATION; PRIOR KNOWLEDGE; REAL-WORLD DATASETS; RECEPTIVE FIELDS; TRAINING PROCESSES;

CLASSIFICATION (OF INFORMATION);

EID: 51949098114     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587592     Document Type: Conference Paper

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