Title :
Shading cues for object class detection
Author :
Stark, Michael ; Goesele, Michael ; Schiele, Bernt
Author_Institution :
Comput. Sci. Dept., Tech. Univ. Darmstadt, Darmstadt, Germany
fDate :
Sept. 27 2009-Oct. 4 2009
Abstract :
Recognition of object classes in natural images has made tremendous progress in recent years. Today´s approaches often rely on powerful learning approaches as well as robust local 2D shape or appearance features. Exploiting 3D shape cues however has become unfashionable in recent literature. While shading cues play a major role in human perception of object shape, shape-from-shading techniques are seldom used today for object class detection. Drawing on ideas from the early days in object recognition this paper aims to revisit the concept of using shading primitives to support object class detection. We demonstrate and discuss the applicability of this approach to real world images of a standard benchmark data set. Experimental results suggest that our shading cues can be useful for object class detection.
Keywords :
computer graphics; image recognition; object detection; object recognition; shape recognition; 3D shape cues; benchmark data set; human perception; natural images; object class detection; object class recognition; robust local 2D shape; shading cues; shape-from-shading techniques; Computer vision; Conferences; Humans; Image recognition; Layout; Object detection; Object recognition; Robustness; Shape control; Surface topography;
Conference_Titel :
Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4244-4442-7
Electronic_ISBN :
978-1-4244-4441-0
DOI :
10.1109/ICCVW.2009.5457640