Unified detection and tracking of humans using gaussian particle swarm optimization 가우시안 입자 군집 최적화를 이용한 사람의 통합된 검출 및 추적

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 498
  • Download : 0
Human detection is a challenging task in many fields because it is difficult to detect humans due to their variable appearance and posture. Furthermore, it is also hard to track the detected human because of their dynamic and unpredictable behavior. The evaluation speed of method is also important as well as its accuracy. In this paper, we propose unified detection and tracking method for humans using Gaussian-PSO (Gaussian Particle Swarm Optimization) with the HOG (Histograms of Oriented Gradients) features to achieve a fast and accurate performance. Keeping the robustness of HOG features on human detection, we raise the process speed in detection and tracking so that it can be used for real-time applications. These advantages are given by a simple process which needs just one linear-SVM classifier with HOG features and Gaussian-PSO procedure for the both of detection and tracking. © ICROS 2012.
Publisher
Institute of Control, Robotics and Systems
Issue Date
2012-04
Language
Korean
Citation

Journal of Institute of Control, Robotics and Systems, v.18, no.4, pp.353 - 358

ISSN
1976-5622
URI
http://hdl.handle.net/10203/104289
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0