PT Chapter
AU Angel Sappa
   David Geronimo
   Fadi Dornaika
   Mohammad Rouhani
   Antonio Lopez
TI Moving object  detection from mobile platforms using stereo data registration
BT Computational Intelligence paradigms in advanced pattern classification
PY 2012
BP 25
EP 37
VL 386
DI 10.1007/978-3-642-24049-2_3
DE pedestrian detection
AB This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and tracked through consecutive 2D frames. Then, a RANSAC based approach is used for registering two point sets, with known correspondences in the 3D space. The computed 3D rigid displacement is used to map two consecutive 3D point clouds into the same coordinate system by means of the quaternion method. Finally, moving objects correspond to those areas with large 3D registration errors. Experimental results show the viability of the proposed approach to detect moving objects like vehicles or pedestrians in different urban scenarios.
ER