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We introduce a new computer vision based system for robust traffic sign recognition and tracking. Such a system presents a vital support for driver assistance in an intelligent automotive. Firstly, a color based segmentation method is applied to generate traffic sign candidate regions. Secondly, the HoG features are extracted to encode the detected traffic(More)
Over the last two decades, the advances in computer vision and pattern recognition power have opened the door to new opportunity of automatic facial expression recognition system. In this work, we have introduced a new feature-based approach for facial expressions recognition. The proposed approach provides full automatic solution to identify human(More)
Human Machine Interaction systems are able to perceive facial expressions more naturally and reliably. In this paper, we introduced a new idea to recognize facial expression by selecting the most discriminative facial regions relying on facial expression appearance. The proposed approach is based on the prior knowledge of psychology studies which show that(More)
This paper presents a new system to achieve face detection and tracking in video sequences. We have performed a combination between detection and tracking modules to overcome the different challenging problems that can occur while detecting or tracking faces. Our proposed system is composed of two modules: Face detection module and face tracking module. In(More)
Accidents caused by reduced concentration of drivers on traffic signs indications continue to represent an important part of accident-prone situations. Face to this threat, our work aims to develop a vision-based traffic sign recognition method based on a two-step recognition and 3D distance computing module. Firstly, a monocular color based segmentation(More)