Laurent Bonnaud

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In this paper we focus on the software design of a multimodal driving simulator that is based on both multimodal driver's focus of attention detection as well as driver's fatigue state detection and prediction. Capturing and interpreting the driver's focus of attention and fatigue state is based on video data (e.g., facial expression , head movement, eye(More)
— This paper presents a driver simulator, which takes into account information about the user's state of mind (level of attention, fatigue state, stress state). The user's state of mind analysis is based on video data and biological signals. Facial movements such as eyes blinking, yawning, head rotations… are detected on video data: they are used in order(More)
This paper introduces a video object segmentation algorithm developed in the context of the European project Art.live 1 where constraints on the quality of segmentation and the processing rate (at least 10 images/second) are required. In order to obtain a fine segmentation (no blocking effect, boundaries precision, temporal stability without flickering),(More)
The problem of multiple people detection in monocular video streams is addressed. The proposed method involves a human model based on skin color and foreground information. Robustness to local motion of background and global color changes is achieved by modeling images as fields of color distributions, and robustly estimating temporal background global(More)
This paper presents a new temporal interpolation algorithm based on segmentation of images into polygonal regions undergoing aane motion. The goal of this work is to improve upon the block-based interpolation used in mpeg (B-frames). In the rst part, we brieey describe the region based framework and the temporal linking algorithm that jointly provide the(More)
— This paper presents various classifiers results from a system that can automatically recognize four different static human body postures in video sequences. The considered postures are standing, sitting, squatting, and lying. The three classifiers considered are a na¨ıve one and two based on the belief theory. The belief theory-based classifiers use(More)
In this paper we present a boundary-based representation of a motion-based image sequence segmentation. A tracking algorithm is associated to this structure which is able to handle several objects simultaneously, in the presence of partial occlusions. This segmentation representation uses the boundaries between all couples of adjacent regions approximated(More)
This paper presents a system that can automatically recognize four different static human body postures for video surveillance applications. The considered postures are standing, sitting, squatting, and lying. The data come from the persons 2D segmentation and from their face localiza-tion. It consists in distance measurements relative to a reference(More)