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http://dx.doi.org/10.13067/JKIECS.2015.10.2.183

Object Detection and Tracking with Infrared Videos at Night-time  

Choi, Beom-Joon (경성대학교 전자공학과)
Park, Jang-Sik (경성대학교 전자공학과)
Song, Jong-Kwan (경성대학교 전자공학과)
Yoon, Byung-Woo (경성대학교 전자공학과)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.10, no.2, 2015 , pp. 183-188 More about this Journal
Abstract
In this paper, it is proposed to detect and track pedestrian and analyse tracking performance with nighttime CCTV video. The detection is performed by a cascade classifier with Haar-like feature trained with Adaboost algorithm. Tracking pedestrian is performed by a particle filter. As results of experiments, it is introduced that efficient number of particles and the distributions are applied to track pedestrian at the night-time. Performance of detection and tracking is verified with nighttime CCTV video that is obtained at alleys etc.
Keywords
Object Detection; Object Tracking; Adaboost Algorithm; Particle filter; Night-Time CCTV video;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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