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NLOOK : a computational attention model for robot vision

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NLOOK : a computational attention model for robot vision

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Título NLOOK : a computational attention model for robot vision
Autor Heinen, Milton Roberto
Engel, Paulo Martins
Abstract The computational models of visual attention, originally proposed as cognitive models of human attention, nowadays are being used as front-ends to some robotic vision systems, like automatic object recognition and landmark detection. However, these kinds of applications have different requirements from those originally proposed. More specifically, a robotic vision system must be relatively insensitive to 2D similarity transforms of the image, as in-plane translations, rotations, reflections and scales, and it should also select fixation points in scale as well as position. In this paper a new visual attention model, called NLOOK, is proposed. This model is validated through several experiments, which show that it is less sensitive to 2D similarity transforms than other two well known and publicly available visual attention models: NVT and SAFE. Besides, NLOOK can select more accurate fixations than other attention models, and it can select the scales of fixations, too. Thus, the proposed model is a good tool to be used in robot vision systems.
Contido em Journal of the Brazilian Computer Society. Porto Alegre. Vol. 15, n. 3 (2009 Sept.), p. 3-17
Assunto Inteligência artificial
Visao computacional
[en] Biomimetic vision
[en] Focus of attention
[en] Robot vision
[en] Selective attention
[en] Visual attention
Origem Nacional
Tipo Artigo de periódico
URI http://hdl.handle.net/10183/72579
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