PSO-Particle Filter-Based Biometric Measurement for Human Tracking
Author(s) -
Zhen-Yuan Xu,
Junzo Watada
Publication year - 2012
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2012.p0533
Subject(s) - biometrics , computer science , tracking (education) , particle filter , artificial intelligence , computer vision , particle swarm optimization , measure (data warehouse) , filter (signal processing) , pattern recognition (psychology) , algorithm , data mining , psychology , pedagogy
Today, security and surveillance systems are required not only to track the motions of humans but also, in some situations, to recognize and measure biometric features such as width and length. Few methods have been proposed for biometric height measurement in human tracking. Some studies have shown that an infrared ray technique can survey the height of a human, but the equipment required is complicated. The objective of this paper is to build a mathematical model to measure the biometrics of human tracking. This tracking method can show humans’ and objects’ size in a picture so that, if we put this picture in a frame of axes, we can calculate the height and other biometric lengths. To obtain the most accurate results for biometric length surveillance, we need a tracking method that is more exact than conventional tracking results. Combining tracking and detection methods using a particle swarm optimization-particle filter shows results with great accuracy in human tracking.
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