1 November 1992 'We do dishes, but we don't do windows': function-based modeling and recognition of rigid objects
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Proceedings Volume 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision; (1992) https://doi.org/10.1117/12.131522
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
Generic recognition for computer vision is a goal that is still far from reality. Part of the problem rests in the inherent limitations of current `model-based' vision. Our approach moves away from specific geometric or structural models and instead focuses on the functionality of the object as the property which drives the recognition process. This results in a representation that is generic in the sense of capturing an entire category of objects. One important assumption underlying the form and function approach is that a `small' number of `primitive' concepts about shape, physics, and causation will suffice to define the functionality of a broad range of categories. If multiple new `primitives' were required to define each additional category, then much of the advantages of the function-based approach over the traditional model-based approach would be lost. This paper presents some initial experimental results from the GRUFF-3 system, which uses function-based representation to recognize rigid objects in the superordinate category dishes. The performance of this system has been evaluated on a database of approximately 200 shapes.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Melanie A. Sutton, Louise Stark, Kevin W. Bowyer, "'We do dishes, but we don't do windows': function-based modeling and recognition of rigid objects", Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); doi: 10.1117/12.131522; https://doi.org/10.1117/12.131522
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