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Independent 3D Motion Detection Through Robust Regression in Depth Layers
 

Summary: Independent 3D Motion Detection
Through Robust Regression in Depth Layers
Antonis A. Argyros, Manolis I.A. Lourakis,
Panos E. Trahanias and Stelios C. Orphanoudakis
Institute of Computer Science, FORTH
PO Box 1385, Heraklion, Crete 711-10
Greece
and
Computer Science Department
University of Crete
PO Box 1470, Heraklion, Crete 714-09
Greece
e-mail: fargyros, lourakis, trahania, orphanoug@ics.forth.gr
Abstract
This paper presents a methodology for the detection of objects that move independently
of the observer in a 3D dynamic environment. Independent 3D motion detection is
formulated as a problem of robust regression applied to visual input acquired by a binocular,
rigidly moving observer. The qualitative analysis of images acquired by a parallel stereo
configuration yields a segmentation of a scene into depth layers. A depth layer consists of
points of the 3D space with almost constant depth from the observer. Robust regression

  

Source: Argyros, Antonis - Foundation of Research and Technology, Hellas & Department of Computer Science, University of Crete

 

Collections: Computer Technologies and Information Sciences