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A probabilistic approach has been developed to extract recurrent serious Occupational Accident with Movement Disturbance (OAMD) scenarios from narrative texts within a prevention framework. Relevant data extracted from 143 accounts was initially coded as logical combinations of generic accident factors. A Bayesian Network (BN)-based model was then built for OAMDs using these data and expert knowledge...
The current study deals with new perspectives to perform more efficient classification of mouse skin precancerous stages by exploiting the spatial resolution of multimodal spectro-scopic data in a decision fusion scheme based on belief functions.
Several approaches have been proposed to recognize human emotions based on facial expressions or physiological signals, relatively rare work has been done to fuse these two, and other, modalities to improve the accuracy and robustness of the emotion recognition system. In this paper, we propose two methods based on feature-level and decision-level to fuse facial and physiological modalities. At feature-level...
This paper presents an automatic approach for emotion recognition from a bimodal system based on facial expressions and physiological signals. The information fusion is to combine information from both modalities. We tested two approaches, one based on mutual information which allows the selection of relevant information, the second approach is based on principal component analysis that allows the...
This paper describes emotion recognition system based on facial expression. A fully automatic facial expression recognition system is based on three steps: face detection, facial characteristic extraction and facial expression classification. We have developed an anthropometric model to detect facial feature points combined to Shi&, Thomasi method. The variations of 21 distances which describe...
The ability to recognize emotion is one of the hallmarks of emotion intelligence. This paper proposed to recognize emotion using physiological signals obtained from multiple subjects. IAPS images were used to elicit target emotions. Five physiological signals: Blood volume pulse (BVP), Electromyography (EMG), Skin Conductance (SC), Skin Temperature (SKT) and Respiration (RESP) were selected to extract...
In this paper, we present a detection and tracking feature points algorithm in real time camera input environment. To trace and extract a face image, we use a modified face detector based on the Haar-like features. For feature points detection, we use good features to track of Shi and Thomasi. In order to track the facial feature points, pyramidal Lucas-Kanade feature tracker algorithm is used. Results...
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