Automatic estimation of pedestrian flow

  • Lee, Gwang Gook
  • Kim, Byeoung Su
  • Kim, Whoi Yul
Citations

SCOPUS

22

초록

Counting the amount of pedestrian flow is an important task for video surveillance applications. Most previous methods for pedestrian flow counting employed model-based detection or top-view cameras to measure pedestrian flow. However, those approaches are difficult to apply to realistic applications because of high complexity or specific camera set up. In this paper, a pixel count based method is proposed for pedestrian flow estimation. In the proposed method, image features such as foreground pixels and motion vectors are utilized as clues to find the number of people going through a gate. To estimate the number of pedestrians without any modeling or tracking, the number of foreground pixels is accumulated on the gate. Experiments on the PETS2006 dataset revealed that the proposed method can count the number of pedestrians successfully even for viewpoint changes.

키워드

Pedestrian flowPeople countingVisual surveillanceCamerasEstimationPixelsAutomatic estimationData setsDistributed smart camerasImage featuresInternational conferencesModel based (OPC)Motion vector (MV)Pedestrian flowsPixel countingRealistic applicationsVideo-surveillance applicationsSecurity systems
제목
Automatic estimation of pedestrian flow
저자
Lee, Gwang GookKim, Byeoung SuKim, Whoi Yul
DOI
10.1109/ICDSC.2007.4357536
발행일
2007-09
유형
Conference Paper
저널명
2007 1st ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC
페이지
291 ~ 296