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      People detection and tracking in videos

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      main article (37.85Mb)
      Author
      Chen, Jiaying
      Date of Issue
      2017-05-16
      School
      School of Electrical and Electronic Engineering
      Abstract
      People detection and tracking in videos have a wide variety of applications in computer vision such as surveillance, people recognition, crowd behavior analysis, human-machine interaction. In this paper, I present some methods for people detection and tracking. Firstly, compared to the original HOG-SVM classifier without hard examples, I used the HOG-SVM classifier with pre-trained hard examples for people detection. Secondly, I proposed a novel method for people detection and tracking. Proposed approach utilizes the deformable part model (DPM) object detector to get people features and detect people positions in the video as well as high speed tracking with kernelized correlation filter (KCF) based tractor to tract the detected person.
      Subject
      DRNTU::Engineering
      Type
      Final Year Project (FYP)
      Rights
      Nanyang Technological University
      Collections
      • EEE Student Reports (FYP/IA/PA/PI)

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