Predicting blocking effects in the spatial domain using a learning approach

A new method for predicting blocking effect in the spatial domain is proposed. This method aims at estimating the appearance of blocking artefacts in the original image prior to compression for a given bit rate and a given compression technique. The basic idea is to use a training process in order to compute a visibility measure. A weighting function of the blocking effects is then derived from this training process performed on a database. The proposed method is objectively and subjectively evaluated on various actual images. The obtained results confirm the efficiency of the proposed method in predicting blocking effect

A synchrony based approach for human robot interaction

As psychologists considered synchrony as an important parameter for social interaction, we hypothesize that in the case of social interaction, people focus their attention on regions of interest where the visual stimuli are synchronized with their inner dynamics. Then, we assume that a mechanism able to detect synchrony between internal dynamics of a robot and external visual stimuli can be used as a starting point for human robot interaction. Inspired by human psychological and neurobiological data, we propose a synchrony based neural network architecture capable of selecting the robot interaction partner and of locating Focus of Attention

Learning to Synchronously Imitate Gestures Using Entrainment Effect

International audienceSynchronisation and coordination are omnipresent and essential in humans interactions. Because of their unavoidable and unintentional aspect, those phenomena could be the consequences of a low level mechanism: a driving force originating from external stimuli called the entrainment effect. In the light of its importance in interaction and wishing to define new HRI, we suggest to model this entrainment to highlight its efficiency for gesture learning during imitative games and for reducing the computational complexity. We will put forward the capacity of adaptation offered by the entrainment effect. Hence, we present in this paper a neural model for gesture learning by imitation using entrainment effect applied to a NAO robot interacting with a human partner

A synchrony based approach for human robot interaction

As psychologists considered synchrony as an important parameter for social interaction, we hypothesize that in the case of social interaction, people focus their attention on regions of interest where the visual stimuli are synchronized with their inner dynamics. Then, we assume that a mechanism able to detect synchrony between internal dynamics of a robot and external visual stimuli can be used as a starting point for human robot interaction. Inspired by human psychological and neurobiological data, we propose a synchrony based neural network architecture capable of selecting the robot interaction partner and of locating Focus of Attention

Social-motor experience and perception-action learning bring efficiency to machines

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A Hough Transform with projection for velocity estimation

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A New Free Reference Image Quality Index Based on Perceptual Blur Estimation

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Real time tracking of multiple persons using elementary tracks

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Objects velocity estimation on images sequences by Hough transform with projection (HTP)

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