Abstract
An effective human-robot interaction is essential for wide penetration of service robots into the market. Such robots need vision systems to recognize objects. It is, however, difficult to realize vision systems that can work in various conditions. More robust techniques of object recognition and image segmentation are essential. Thus, we have proposed to use the human user’s assistance for objects recognition through speech. Our previous system assumes that it can segment images without failure. However, if there are occluded objects and/or objects composed of multicolor parts, segmentation failures cannot be avoided. This paper presents an extended system that can recognize objects in occlusion and/or multicolor cases using geometric and photometric analysis of images. If the robot is not sure about the segmentation results, it asks questions of the user by appropriate expressions depending on the certainty to remove the ambiguity.
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Hossain, M.A., Kurnia, R., Kuno, Y. (2005). Geometric and Photometric Analysis for Interactively Recognizing Multicolor or Partially Occluded Objects. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_17
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DOI: https://doi.org/10.1007/11595755_17
Publisher Name: Springer, Berlin, Heidelberg
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