Derivation of motion characteristics using affine shape adaptation for moving blobs

Abstract

This chapter applies anisotropic Gaussian scale space theory for modeling affine shape modifications of moving blobs in the context of vision-based driver assistance systems. First, affine blobs are detected in an image sequence and tracked; second, their scale ratios are used for the derivation of 3D motion characteristics. For example, this also allows to estimate the navigation angles of a moving camera in 3D space. The theoretical concept is explained in detail, and illustrated by a few experiments, including an indoor experiment and also the estimation of navigation angles of a car (i.e., of the ego-vehicle) in provided test sequences. The numerical evaluations indicate the validity of the idea and advantages to vehicle vision. © 2009 Springer-Verlag.