Title :
Detection of multi-part objects by top-down perceptual grouping
Author :
Randrianarisoa, Vénérée ; Bernier, Jean-François ; Bergevin, Robert
Author_Institution :
Lab. de Vision et Systemes Numeriques (LVSN), Univ. Laval, Sainte-Foy, Que., Canada
Abstract :
In this paper, a top-down approach based on perceptual grouping is proposed for multi-part objects detection. The abstract conceptual category of multi-part objects is formalized by a set of global criteria. These criteria will enable the evaluation of the segmentation quality in order to determine if the whole grouping is perceptually significant and if it has a good perceptual shape. A new cognitive vision methodology, called SAFE (subjectivity and formalism explicitly), is presented. Its goal is to help identify the proper global criteria and to validate the judgment derived from formal calculations of these criteria by human judgment.
Keywords :
image segmentation; object detection; SAFE; abstract conceptual category; multipart object detection; top-down perceptual grouping; Computational efficiency; Computer vision; Humans; Image segmentation; Layout; Object detection; Object recognition; Pixel; Shape; Visual system; methodology; object detection; perceptual grouping; top-down processing;
Conference_Titel :
Computer and Robot Vision, 2005. Proceedings. The 2nd Canadian Conference on
Print_ISBN :
0-7695-2319-6
DOI :
10.1109/CRV.2005.34