Video analysis-based vehicle detection and tracking using an MCMC sampling framework

Eurasip Journal on Advances in Signal Processing

Volumn 2012, Issue 1, 2012, Pages

  Arróspide, Jon ^a   Salgado, Luis ^a   Nieto, Marcos ^b  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

^b VICOMTECH   (Spain)

Author keywords

HOG; Intelligent vehicles; Monte Carlo methods; Object tracking

Indexed keywords

BAYESIAN METHODS; DESCRIPTORS; EFFICIENT SAMPLING; FEATURE SPACE; FILTER-BASED; GRADIENT ORIENTATIONS; HOG; IN-VEHICLE; INTER-DEPENDENCIES; MARKOV CHAIN MONTE CARLO; MARKOV RANDOM FIELDS; MCMC SAMPLING; MONOCULAR IMAGE; MOTION MODELS; MOTION PARALLAX; MULTIPLE OBJECTS; OBJECT TRACKING; OBSERVATION MODEL; PARTICLE FILTERING; PROBABILISTIC METHODS; REAL-TIME APPLICATION; SUPERVISED CLASSIFICATION; TEST SEQUENCE; TRACKING METHOD; TRAFFIC ENVIRONMENT; VEHICLE DETECTION; VEHICLE IMAGES;

BAYESIAN NETWORKS; GEOMETRICAL OPTICS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MONTE CARLO METHODS; SIGNAL FILTERING AND PREDICTION; SUPPORT VECTOR MACHINES; TEMPLATE MATCHING;

TRACKING (POSITION);

EID: 84864999648     PISSN: 16876172     EISSN: 16876180     Source Type: Journal    
DOI: 10.1186/1687-6180-2012-2     Document Type: Article

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