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Title: Visual attention and perception in scene understanding for social robotics
Keywords: saliency, attention, head-eye coordination, dimension reduction, scene understanding, social robotics
Issue Date: 31-May-2012
Citation: HE HONGSHENG (2012-05-31). Visual attention and perception in scene understanding for social robotics. ScholarBank@NUS Repository.
Abstract: The objective of this research was to endow social robots with the capabilities of visual attention, perception and response in a biological manner for natural human-robot interaction. The visual saliency is quantified by measuring color attraction, information scale and object context. Together with the visual saliency, the visual attention was predicted by fusing the motion saliency and common attention from prior knowledge. Towards the predicted attention, the robotic head was designed to behave naturally by following biological laws of the head and eye coordination during saccades and gazes. The nonlinear dimension reduction algorithm named Geometrically Local Embedding (GLE) and its linearization Locally Geometrical Projection (LGP) were also proposed for information presentation and perception of social robots. The proposed approaches can improve the social sense of social robots and user experience by equipping them with the abilities to determine their attention autonomously, perceive and behave naturally in human-robot interaction.
Appears in Collections:Ph.D Theses (Open)

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