Learn More
Visual attention is the ability of the human vision system to detect salient parts of the scene, on which higher vision tasks, such as recognition, can focus. In human vision, it is believed that visual attention is intimately linked to the eye movements and that the fixation points correspond to the location of the salient scene parts. In computer vision,(More)
Visual attention is the ability of a vision system, be it biological or artificial, to rapidly detect potentially relevant parts of a visual scene, on which higher level vision tasks, such as object recognition, can focus. The saliency-based model of visual attention represents one of the main attempts to simulate this visual mechanism on computers. Though(More)
This paper is a contribution to automatic speaker recognition. It considers speech analysis by linear prediction and investigates the recognition contribution of its two main resulting components, namely the synthesis filter on one hand and the residue on the other hand. This investigation is motivated by the orthogonality property and the physiological(More)
Visual attention is the ability to rapidly detect the visually salient parts of a given scene on which higher level vision tasks, such as object recognition, can focus. Found in biological vision, this mechanism represents a fundamental tool for computer vision. This paper reports the first real-time implementation of the complete visual attention mechanism(More)
Visual attention is the ability to rapidly detect the interesting parts of a given scene on which higher level computer vision tasks can focus. This paper reports a computational model of dynamic visual attention which combines static and dynamic features to detect salient locations in natural image sequences. Therefore, the model computes a map of(More)
Manual object digitizing is a tedious task and can be replaced by 3D scanners which provide an accurate and fast way to digitize solid objects. Since only one view of an object can be captured at once, several views have to be combined in order to obtain a description of the complete surface. In this paper a digitizing system is proposed which captures and(More)
The iterative closest point (ICP) algorithm is widely used for the registration of 3D geometric data. One of the main drawbacks of the algorithm is its quadratic time complexity O(N 2) with the number of points N. Consequently, several methods have been proposed to accelerate the process. This paper presents a new solution for the speeding up of the ICP(More)