Authors:
Ahmed Derbel
1
;
Yousra Ben Jemaa
2
;
Sylvie Treuillet
3
;
Bruno Emile
3
;
Raphael Canals
3
and
Abdelmajid Ben Hamadou
1
Affiliations:
1
SFAX University, Tunisia
;
2
TUNIS University, Tunisia
;
3
ORLEANS University, France
Keyword(s):
People Identification and Tracking, Multi-camera, Cascade of Descriptors, AdaBoost, Cumulative Matching
Characteristic.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Camera Networks and Vision
;
Computer Vision, Visualization and Computer Graphics
Abstract:
In this paper, we introduce a new approach to identify people in multi-camera based on AdaBoost descriptors
cascade. Given the complexity of this task, we propose a new regional color feature vector based on intra and
inter color histograms fusion to characterize a person in multi-camera. This descriptor is then integrated into
an extensive comparative study with several existing color, texture and shape feature vectors in order to choose
the best ones. We prove through a comparative study with the main existing approaches on the VIPeR dataset
and using Cumulative Matching Characteristic measurement that the proposed approach is very suitable to
identify a person and provides very satisfactory performances.