Esther Antúnez

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In biological vision systems, attention mechanisms are responsible for selecting the relevant information from the sensed field of view, so that the complete scene can be analyzed using a sequence of rapid eye saccades. In recent years, efforts have been made to imitate such attention behavior in artificial vision systems, because it allows optimizing the(More)
This paper introduces a new method to represent the surface of objects using two dimensional com-binatorial maps. The classical definition of two dimensional combinatorial maps is extended here by adding a " back face " that corresponds to the non–visible part of the object. As a first step, every object in the scene is extracted in one image pyramid, where(More)
This paper describes a visual landmark detection and description system for mobile robotic environment mapping. At the detection stage, the paper employs a perceptual–based hierarchical algorithm which has been previously used for segmentation of natural images. At the description stage, visual landmarks are characterized by a kernel–based representation(More)
Computer vision systems have to deal with thousands, sometimes millions of pixel values from each frame, and the computational complexity of many problems related to the interpretation of image data is very high. The task becomes especially difficult if a system has to operate in real-time. Within the Combinatorial Pyramid framework, the proposed(More)
Scene understanding and other high-level visual tasks usually rely on segmenting the captured images for dealing with a more efficient mid-level representation. Although this segmentation stage will consider topological constraints for the set of obtained regions (e.g., their internal connectivity), it is typical that the importance of preserving the(More)