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Derivation of Motion Characteristics Using Affine Shape Adaptation for Moving Blobs

  • Jorge Sanchez
  • Reinhard Klette
  • Eduardo Destefanis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5604)

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.

Keywords

Characteristic Scale Motion Characteristic Integration Scale Moment Matrix Scale Selection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jorge Sanchez
    • 1
  • Reinhard Klette
    • 2
  • Eduardo Destefanis
    • 1
  1. 1.Universidad Tecnológica NacionalCordobaArgentina
  2. 2.The .enpeda.. Project, The University of AucklandNew Zealand

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