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Fast Human Detection Using Deformable Part Model at the Selected Candidate Detection Positions

  • Xiaotian WuEmail author
  • KyoungYeon Kim
  • Guoyin Wang
  • Yoo-Sung Kim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9436)

Abstract

We integrate the classic deformable part models (DPM) with the object proposal approaches to achieve a fast and accurate human detection system. The proposed method avoids exhaustive sliding window search, which accelerating the detection speed and reducing the incorrect false positives. In this paper, EdgeBoxes and BING are selected as the candidate object proposal methods to generate the candidate detection positions for the DPM, because their good performance and fast speed. The DPM is only carried on the candidate locations selected by EdgeBoxes and BING for fast human detection. Experiments on PASCAL 2007 dataset for human detection show that the proposed method accelerates the detection speed and reduces the incorrect detections effectively, and EdgeBoxes is better than BING.

Keywords

Human detection Deformable part model Object proposals Sliding windows Candidate positions 

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© Springer International Publishing Switzerland 2015

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Authors and Affiliations

  • Xiaotian Wu
    • 1
    Email author
  • KyoungYeon Kim
    • 2
  • Guoyin Wang
    • 1
  • Yoo-Sung Kim
    • 2
  1. 1.Key Laboratory of Chongqing Computation and IntelligenceChongqing University of Posts and TelecommunicationsChongqingPeople’s Republic of China
  2. 2.Department of Information and Communication EngineeringInha UniversityIncheonKorea

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