TY - JOUR
T1 - Moving object detection from mobile platforms using stereo data registration
AU - Sappa, Angel D.
AU - Gerónimo, David
AU - Dornaika, Fadi
AU - Rouhani, Mohammad
AU - López, Antonio M.
PY - 2012/2/6
Y1 - 2012/2/6
N2 - 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. © 2012 Springer-Verlag Berlin Heidelberg.
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. © 2012 Springer-Verlag Berlin Heidelberg.
U2 - 10.1007/978-3-642-24049-2_3
DO - 10.1007/978-3-642-24049-2_3
M3 - Article
VL - 386
SP - 25
EP - 37
JO - Studies in Computational Intelligence
JF - Studies in Computational Intelligence
SN - 1860-949X
ER -