Thomas G. Smith

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—An important goal in studying both human intelligence and artificial intelligence is to understand how a natural or an artificial learning system deals with the uncertainty and ambiguity of the real world. For a natural intelligence system such as a human toddler, the relevant aspects in a learning environment are only those that make contact with the(More)
Multimodal interaction in everyday life seems so effortless. However, a closer look reveals that such interaction is indeed complex and comprises multiple levels of coordination, from high-level linguistic exchanges to low-level couplings of momentary bodily movements both within an agent and across multiple interacting agents. A better understanding of how(More)
Data-driven knowledge discovery is becoming a new trend in various scientific fields. In light of this, the goal of the present paper is to introduce a novel framework to study one interesting topic in cognitive and behavioral studies -multimodal communication between human-human and human-robot interaction. We present an overall solution from data capture,(More)
With advances in computing techniques, a large amount of high-resolution high-quality multimedia data (video and audio, etc.) has been collected in research laboratories in various scientific disciplines, particularly in social and behavioral studies. How to automatically and effectively discover new knowledge from rich multimedia data poses a compelling(More)
Studies suggest that visual attention, guided in part by features' visual salience, is necessary for change detection. An image processing algorithm was used for measuring the visual salience of the features of scenes, and participants' ability to detect changes made to high and low salience features was measured with a flicker paradigm while their eye(More)
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