Multimedia Tools and Applications

, Volume 75, Issue 11, pp 6263–6282 | Cite as

Fast moving pedestrian detection based on motion segmentation and new motion features

  • Shanshan Zhang
  • Dominik A. Klein
  • Christian Bauckhage
  • Armin B. Cremers
Article

Abstract

The detection of moving pedestrians is of major importance for intelligent vehicles, since information about such persons and their tracks should be incorporated into reliable collision avoidance algorithms. In this paper, we propose a new approach to detect moving pedestrians aided by motion analysis. Our main contribution is to use motion information in two ways: on the one hand we localize blobs of moving objects for regions of interest (ROIs) selection by segmentation of an optical flow field in a pre-processing step, so as to significantly reduce the number of detection windows needed to be evaluated by a subsequent people classifier, resulting in a fast method suitable for real-time systems. On the other hand we designed a novel kind of features called Motion Self Difference (MSD) features as a complement to single image appearance features, e. g. Histograms of Oriented Gradients (HOG), to improve distinctness and thus classifier performance. Furthermore, we integrate our novel features in a two-layer classification scheme combining a HOG+Support Vector Machines (SVM) and a MSD+SVM detector. Experimental results on the Daimler mono moving pedestrian detection benchmark show that our approach obtains a log-average miss rate of 36 % in the FPPI range [10−2,100], which is a clear improvement with respect to the naive HOG+SVM approach and better than several other state-of-the-art detectors. Moreover, our approach also reduces runtime per frame by an order of magnitude.

Keywords

Pedestrian detection Motion segmentation Motion self difference features Histograms of oriented gradients Support vector machines 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Shanshan Zhang
    • 1
  • Dominik A. Klein
    • 2
  • Christian Bauckhage
    • 3
  • Armin B. Cremers
    • 1
  1. 1.Institute of Computer Science IIIUniversity of BonnBonnGermany
  2. 2.Fraunhofer FKIEWachtbergGermany
  3. 3.Fraunhofer IAISSankt AugustinGermany

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