Authors:
Cyrille Migniot
;
Pascal Bertolino
and
Jean-Marc Chassery
Affiliation:
CNRS Gipsa-Lab DIS, France
Keyword(s):
Human detection and segmentation, Silhouette, Histograms of oriented gradients.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Implementation of Image and Video Processing Systems
;
Informatics in Control, Automation and Robotics
;
Segmentation and Grouping
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
Human detection and segmentation is a challenging task owing to variations in human pose and clothing. The union of Histograms of Oriented Gradients based descriptors and of a Support Vector Machine classifier is a classic and efficient method for human detection in the images. Conversely, as often in detection, accurate segmentation of these persons is not performed. Many applications however need it. This paper tackles the problem of giving rise to information that will guide the final segmentation step. It presents a method which uses the union mention above to relate to each contour segment a likelihood degree of being part of a human silhouette. Thus, data previously computed in detection are used in the pre-segmentation. A human silhouette database was ceated for learning.