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Multimedia Tools and Applications

, Volume 76, Issue 18, pp 18321–18337 | Cite as

Shadow removal for pedestrian detection and tracking in indoor environments

  • Lingxiang Zheng
  • Xiaoyang Ruan
  • Yunbiao Chen
  • Minzheng Huang
Article

Abstract

This paper presents a method of shadow removal to improve the accuracy of pedestrian detection and tracking in indoor environments. The proposed method can be divided into four steps: building a background model which can be automatically updated, extract moving objects region, eliminating moving objects shadows, classifying and track pedestrians. The background model is built with pixel value and the updating of Gussian. The approach for real time background-foreground extraction is used to extract pedestrian region that may contains multiple shadows. In the gray histogram space, based on the depth value of the gray images, a reasonable threshold is set to remove shadows from various pedestrians. In this work, we propose a methodology using the foreground frames without shadows to detect and track the pedestrians across training datasets. Comparative experimental results show that our method is capable of dealing with shadows and detecting moving pedestrians in cluttered environments.

Keywords

Background elimination Shadow removal Gray histogram space Pedestrian detectiing Pedestrian tracking 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Lingxiang Zheng
    • 1
  • Xiaoyang Ruan
    • 1
  • Yunbiao Chen
    • 1
  • Minzheng Huang
    • 1
  1. 1.School of Information Science and EngineeringXiamen UniversityXiamenChina

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