A genetic algorithm for target tracking in FLIR video sequences using intensity variation function

IEEE Transactions on Instrumentation and Measurement

Volumn 58, Issue 10, 2009, Pages 3457-3467

  Paravati, Gianluca ^a   Sanna, Andrea ^a   Pralio, Barbara ^a   Lamberti, Fabrizio ^a  

^a POLITECNICO DI TORINO   (Italy)

Author keywords

Forward looking infrared (FLIR) imagery; Genetic algorithms (GAs); Image sequence analysis; Infrared (IR) target tracking; Intensity variation function (IVF)

Indexed keywords

ALTERNATIVE APPROACH; AUTOMATIC TARGET TRACKING; COMPLEX SPACE; COMPUTATIONAL COSTS; DATA SETS; EVOLUTIONARY APPROACH; EVOLUTIONARY COMPUTATIONS; FORWARD LOOKING INFRARED; FORWARD-LOOKING INFRARED (FLIR) IMAGERY; GENETIC VARIATION; IMAGE SEQUENCE ANALYSIS; IMPROVING PERFORMANCE; INFRARED (IR) TARGET TRACKING; INTENSITY PROFILES; INTENSITY VARIATION FUNCTION (IVF); INTENSITY VARIATION FUNCTIONS; NATURAL SELECTION RULE; NEAR-OPTIMAL SOLUTIONS; OPTIMIZATION TECHNIQUES; PARALLEL SEARCH; PROCESSING TIME; REAL TIME REQUIREMENT; RESEARCH AREAS; SEARCH METHOD; SOLUTION SPACE; TARGET SEARCH; VIDEO SEQUENCES;

AUTOMATIC TARGET RECOGNITION; COMPUTER VISION; GASES; GENES; GENETIC ALGORITHMS; LIGHT MEASUREMENT; MATHEMATICAL OPERATORS; OPTIMIZATION; TARGETS; VIDEO RECORDING;

TARGET TRACKING;

EID: 70349445109     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIM.2009.2017665     Document Type: Article

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