Multiple hypothesis tracking for cluttered biological image sequences

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 35, Issue 11, 2013, Pages 2736-2750

  Chenouard, Nicolas ^a,b   Bloch, Isabelle ^c   Olivo Marin, Jean Christophe ^a,b  

^a INSTITUT PASTEUR   (France)

^b CNRS   (France)

^c INSTITUT TELECOM   (France)

Author keywords

biological imaging; cluttered images; multiple hypothesis tracking; Particle tracking; target perceivability

Indexed keywords

BIOLOGICAL IMAGING; CLUTTERED IMAGES; MULTIPLE HYPOTHESIS TRACKING; PARTICLE TRACKING; TARGET PERCEIVABILITY;

ALGORITHMS; COMMUNICATION CHANNELS (INFORMATION THEORY); COMPUTER VISION;

TARGET TRACKING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; STATISTICAL ANALYSIS; STATISTICAL MODEL; PROCEDURES;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; SUBTRACTION TECHNIQUE;

EID: 84884580799     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2013.97     Document Type: Article

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