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Stereo-Based Pedestrian Detection for Collision-Avoidance Applications

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3 Author(s)
Nedevschi, S. ; Fac. of Autom. & Comput. Sci., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania ; Bota, S. ; Tomiuc, C.

Pedestrians are the most vulnerable participants in urban traffic. The first step toward protecting pedestrians is to reliably detect them. We present a new approach for standing- and walking-pedestrian detection, in urban traffic conditions, using grayscale stereo cameras mounted on board a vehicle. Our system uses pattern matching and motion for pedestrian detection. Both 2-D image intensity information and 3-D dense stereo information are used for classification. The 3-D data are used for effective pedestrian hypothesis generation, scale and depth estimation, and 2-D model selection. The scaled models are matched against the selected hypothesis using high-performance matching, based on the Chamfer distance. Kalman filtering is used to track detected pedestrians. A subsequent validation, based on the motion field's variance and periodicity of tracked walking pedestrians, is used to eliminate false positives.

Published in:

Intelligent Transportation Systems, IEEE Transactions on  (Volume:10 ,  Issue: 3 )