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Efficient learning from massive amounts of information is a hot topic in computer vision. Available training sets contain many examples with several visual descriptors, a setting in which current batch approaches are typically slow and does not scale well. In this work we introduce a theoretically motivated and efficient online learning algorithm for the Multi Kernel Learning (MKL) problem. For this...
Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled approach to combine multiple cues, and to obtain state-of-the-art performance. A general drawback of these strategies is the high computational cost during training, that prevents their application to large-scale problems. They also do not provide theoretical guarantees on their convergence rate...
To fulfill the dream of having autonomous robots at home, there is a need for spatial representations augmented with semantic concepts. Vision has emerged recently as the key modality to recognize semantic categories like places (office, corridor, kitchen, etc). A crucial aspect of these semantic place representations is that they change over time, due to the dynamism of the world. This calls for...
Learning from sensory patterns associated with different kinds of sensors is paramount for biological systems, as it permits them to cope with complex environments where events rarely appear twice in the same way. In this paper we want to investigate how perceptual categories formed in one modality can be transferred to another modality in biological and artificial systems. We first present a study...
The state-of-the-art in control of hand prosthetics is far from optimal. The main control interface is represented by surface electromyography (EMG): the activation potentials of the remnants of large muscles of the stump are used in a non-natural way to control one or, at best, two degrees-of-freedom. This has two drawbacks: first, the dexterity of the prosthesis is limited, leading to poor interaction...
We consider the problem of estimating the relative orientation of a number of individual photocells-or pixels-that hold fixed relative positions. The photocells measure the intensity of on a pencil of lines. We assume that the light-field thus sampled is changing, e.g. as the result of motion of the sensors and use the obtained measurements to estimate the orientations of the photocells. We explore...
Retinal prosthesis represents the best near-term hope for individuals with chronic blinding disease of the outer retina. However the small number of stimulating electrodes produces a poor, low resolution image. We propose a new preprocessing method for epi-retinal implants and validate it through a novel simulation of the implanted blind perception. Twenty-one normally sighted, untrained subjects...
One of the first steps of any visual system is that of locating suitable interest points, "salient regions", in the scene, to detect events, and eventually to direct gaze toward these locations. In the last few years, object-based visual attention models have received an increasing interest in the literature, the problem, in this case, being that of creating a model of "objecthood"...
This paper describes a developmental sequence that allows a humanoid robot to learn about the shape of its body and successively about certain parts of the environment. We equipped the humanoid robot with an initial set of motor and perceptual competencies ranging from simple stereotyped actions to more sophisticated visual routines providing a bottom-up attention system. This initial form of sensorimotor...
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