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- W2897737748 abstract "Orienting attention towards another person of interest is a fundamental social behaviour prevalent in human-human interaction and crucial in human-robot interaction. This orientation behaviour is often governed by the received audio-visual stimuli. We present an adaptive neural circuit for multisensory attention orientation that combines auditory and visual directional cues. The circuit learns to integrate sound direction cues, extracted via a model of the peripheral auditory system of lizards, with visual directional cues via deep learning based object detection. We implement the neural circuit on a robot and demonstrate that integrating multisensory information via the circuit generates appropriate motor velocity commands that control the robot’s orientation movements. We experimentally validate the adaptive neural circuit for co-located human target and a loudspeaker emitting a fixed tone." @default.
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- W2897737748 date "2018-01-01" @default.
- W2897737748 modified "2023-09-23" @default.
- W2897737748 title "Towards Crossmodal Learning for Smooth Multimodal Attention Orientation" @default.
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- W2897737748 doi "https://doi.org/10.1007/978-3-030-05204-1_31" @default.
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