Abstract
In this paper we propose an approach to distinguish affordances on a fine-grained scale. We define an anthropomorphic agent model and parameterized affordance models. The agent model is transformed according to affordance parameters to detect affordances in the input data. We present first results on distinguishing two closely related affordances derived from sitting. The promising results support our concept of fine-grained affordance detection.
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© 2015 Springer International Publishing Switzerland
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Seib, V., Wojke, N., Knauf, M., Paulus, D. (2015). Detecting Fine-Grained Affordances with an Anthropomorphic Agent Model. In: Agapito, L., Bronstein, M., Rother, C. (eds) Computer Vision - ECCV 2014 Workshops. ECCV 2014. Lecture Notes in Computer Science(), vol 8926. Springer, Cham. https://doi.org/10.1007/978-3-319-16181-5_30
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DOI: https://doi.org/10.1007/978-3-319-16181-5_30
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