Robust People Counting System Based on Sensor Fusion

  • Dan, Byoung-Kyu
  • Kim, You-Sun
  • Suryanto
  • Jung, June-Young
  • Ko, Sung-Jea
Citations

WEB OF SCIENCE

35
Citations

SCOPUS

49

초록

This paper presents a novel robust people counting system based on fusing the depth and vision data. Conventional algorithms utilize the monoscopic or stereoscopic vision data to count people. However, these vision-based people counting methods often fail due to occasional illumination change and crowded environment. In the proposed algorithm, both the top-view vision and depth images are captured by a video-plus-depth camera mounted on the ceiling. The depth image is first processed by a morphological operator to alleviate depth artifacts such as the optical noise and lost data. Then the human object is extracted using a human model from the preprocessed depth image. Finally, the trajectory of the detected object is established by applying the bidirectional matching algorithm. Experimental results show that the proposed algorithm achieves over 98% accuracy in various testing environments(1).

키워드

Surveillance systempeople countingdepth camerasensor fusingobject detection
제목
Robust People Counting System Based on Sensor Fusion
저자
Dan, Byoung-KyuKim, You-SunSuryantoJung, June-YoungKo, Sung-Jea
DOI
10.1109/TCE.2012.6311350
발행일
2012-08
유형
Article
저널명
IEEE Transactions on Consumer Electronics
58
3
페이지
1013 ~ 1021