Mihaela Gordan

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In this paper we proposed a visual speech recognition network based on Support Vector Machines. Each word of the dictionary is modeled by a set of temporal sequences of visemes. Each viseme is described by a support vector machine, and the temporal character of speech is modeled by integrating the support vector machines as nodes into Viterbi decoding(More)
Visual speech recognition is an emerging research field. In this paper, we examine the suitability of support vector machines for visual speech recognition. Each word is modeled as a temporal sequence of visemes corresponding to the different phones realized. One support vector machine is trained to recognize each viseme and its output is converted to a(More)
In this paper we propose a visual speech recognition network based on Support Vector Machines. Each word of the dictionary is described as a temporal sequence of visemes. Each viseme is described by a support vector machine, and the temporal character of speech is modeled by integrating the support vector machines as nodes into a Viterbi decoding lattice.(More)
Many existing works in face recognition are based solely on visible images. The use of bimodal systems based on visible and thermal images is seldom reported in face recognition, despite its advantage of combining the discriminative power of both modalities, under expressions or pose variations. In this paper, we investigate the combined advantages of(More)
The perspective projection models the way a 3D scene is transformed into a 2D image, usually through a camera or an eye. In a projective transformation, parallel lines intersect in a point called vanishing point. This paper presents in detail two calibration methods that exploit the properties of vanishing points. The aim of the paper is to offer a(More)
Liver segmentation from computer tomography scans is a topic of research interest, as the acquisition and inter-patient variability make the automatic segmentation difficult. The current trend is to improve the accuracy and to reduce the computational complexity of the segmentation, as this is essential for the diagnostic and for 3D rendering. We propose a(More)
This paper introduces the vanishing points to self-calibrate a structured light system. The vanishing points permit to automatically remove the projector’s keystone effect and then to self-calibrate the projector–camera system. The calibration object is a simple planar surface such as a white paper. Complex patterns and 3D calibrated objects are not(More)
Speech recognition based on visual information is an emerging research field. We propose here a new system for the recognition of visual speech based on support vector machines which proved to be powerful classifiers in other visual tasks. We use support vector machines to recognize the mouth shape corresponding to different phones produced. To model the(More)
The problem of lip contour detection is critical in the lipreading systems based on contour processing. The typical contour detection strategy based on image segmentation in homogeneous regions fails in the case when the mouth images available for lipreading are lowcontrast gray level images. Most of the solutions adopted require manual marking of some(More)
Support vector machines (SVMs) are powerful classifiers, with very good recognition rates in image analysis tasks. However their computational time in the object recognition phase is often large due to the number of classifications per scene and to the feature vector size, especially when the feature space is formed from raw image data. Several methods are(More)