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Independent 3D Motion Detection Through Robust Regression
 

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
fargyros, lourakis, trahania, orphanoug@ics.forth.gr
Abstract
This paper presents a novel method for the detection of objects that
move independently of the observer in a 3D dynamic environment. In-
dependent 3D motion detection is formulated as a problem of robust
regression applied to visual input acquired by a binocular, rigidly mov-
ing observer. The qualitative analysis of images acquired by a parallel
stereo con guration yields a segmentation of a scene into depth lay-
ers. A depth layer consists of points of the 3D space for which depth
variations are small compared to the distance from the observer. Ro-

  

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

 

Collections: Computer Technologies and Information Sciences