An HMM/MRF-based stochastic framework for robust vehicle tracking

IEEE Transactions on Intelligent Transportation Systems

Volumn 5, Issue 3, 2004, Pages 142-154

  Kato, Jien ^a   Watanabe, Toyohide ^a   Joga, Sébastien ^b   Liu, Ying ^c   Hase, Hiroyuki ^d  

^a NAGOYA UNIVERSITY   (Japan)

^b ORANGE LABS   (France)

^c UNIVERSITY OF TOYAMA   (Japan)

^d UNIVERSITY OF FUKUI   (Japan)

Author keywords

Hidden Markov model (HMM); Image classification; Image segmentation; Markov random field (MRF); Traffic surveillance; Vehicle tracking

Indexed keywords

COMPUTER VISION; IMAGE SEGMENTATION; IMAGING TECHNIQUES; INFORMATION RETRIEVAL; LIGHTING; MARKOV PROCESSES; OPTIMIZATION; PROBLEM SOLVING; RELAXATION PROCESSES; SENSORS; STOCHASTIC PROGRAMMING; TRACKING (POSITION); VEHICLES;

HIDDEN MARKOV MODEL (HMM); IMAGE CLASSIFICATION; INTELLIGENT TRANSPORTATION SYSTEMS (ITS); MARKOV RANDOM FIELD (MRF); TRAFFIC SURVEILLANCE; VEHICLE TRACKING; VISUAL MOTION ANALYSIS;

INTELLIGENT VEHICLE HIGHWAY SYSTEMS;

EID: 4544236170     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2004.833791     Document Type: Article

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