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A Novel Combination Feature HOG-LSS for Pedestrian Detection

  • Shihong Yao
  • Tao Wang
  • Weiming Shen
  • Yanwen Chong
Part of the Communications in Computer and Information Science book series (CCIS, volume 375)

Abstract

Since the ability of various kinds of feature descriptor is different in pedestrian detection and selecting them is not always fathomed, the six common features are analyzed in theory and compared in experiments. It is expected to find a new feature with the strongest description ability from their pair-wise combinations. In experiments, INRIA database and Daimler database are selected as the sample set. Adaboost is regarded as classifier and the detection performance is evaluated by detection rate, false alarm rate and detection time. The results of these three indicators further prove that description ability of HOG-LSS feature is better than others.

Keywords

pedestrian detection feature combination Adaboost 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Shihong Yao
    • 1
  • Tao Wang
    • 1
  • Weiming Shen
    • 1
  • Yanwen Chong
    • 1
  1. 1.State Key Laboratory for Information Engineering in Surveying , Mapping and Remote SensingWuhan UniversityWuhanChina

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