In this paper, a statistical learning approach to spatial context exploitation for semantic image analysis is presented. The proposed method constitutes an extension of the key pa...
Motion estimation is known to be a non-convex optimization problem. This non-convexity comes from several ambiguities in motion estimation such as the aperture problem, or fast mo...
As the resolution of output device increases, the demand of high resolution contents has become more eagerly. Therefore, the image superresolution algorithms become more important....
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
This paper proposes a frequency method to estimate the state open or closed of eye and mouth and to detect associated motion events such as blinking and yawning. The context of th...