Search results for "facial expression recognition"
showing 3 items of 3 documents
Eigenexpressions: Emotion Recognition Using Multiple Eigenspaces
2013
This paper presents an appearance-based holistic method for expression recognition. A two stage supervised learning approach is used. At the first stage, training images are used to compute one subspace per expression. At the second stage, the same images are used to train a classifier. In this step, Euclidean distances from each image to each particular subspace are used as the input to the classifier. The resulting system significantly outperforms the baseline eigenfaces method on the Cohn-Kanade data set, with performance gains in the range 10%-20%.
Time Unification on Local Binary Patterns Three Orthogonal Planes for Facial Expression Recognition
2019
International audience; Machine learning has known a tremendous growth within the last years, and lately, thanks to that, some computer vision algorithms started to access what is difficult or even impossible to perceive by the human eye. While deep learning based computer vision algorithms have made themselves more and more present in the recent years, more classical feature extraction methods, such as the ones based on Local Binary Patterns (LBP), still present a non negligible interest, especially when dealing with small datasets. Furthermore, this operator has proven to be quite useful for facial emotions and human gestures recognition in general. Micro-Expression (ME) classification is…
Recognition of emotional states by visual facial analysis and machine learning
2018
In face-to-face settings, an act of communication includes verbal and emotional expressions. From observation, diagnosis and identification of the individual's emotional state, the interlocutor will undertake actions that would influence the quality of the communication. In this regard, we suggest to improve the way that the individuals perceive their exchanges by proposing to enrich the textual computer-mediated communication by emotions felt by the collaborators. To do this, we propose to integrate a real time emotions recognition system in a platform “Moodle”, to extract them from the analysis of facial expressions of the distant learner in collaborative activities. There are three steps…