Title :
Indexing function-based categories for generic recognition
Author :
Stark, L. ; Bowyer, Kevin
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
Abstract :
The authors report the implementation and evaluation of a function-based recognition system that takes an uninterrupted 3-D object shape as its input and reasons to determine if the object belongs to the superordinate category furniture, and if so, into which (sub)category it falls. The system has analyzed over 250 input objects, and the results largely agree with intuitive human interpretation of the objects. The study confirms that a relatively small number of knowledge primitives may be used as the basis for defining a relatively broad range of object categories. The greatest derivation from intuitive human interpretation occurs with objects that humans would not typically label as one of the known categories defined, but which have some novel orientation in which they could serve the function of one of these categories. This is because the system uses a purely function-based definition of the object category.<>
Keywords :
image recognition; function-based recognition system; generic recognition; indexing; knowledge primitives; object categories; uninterrupted 3D object shape; Computer science; Indexing; Object recognition; Physics; Shape measurement; Solid modeling; Spatial databases; Testing; Visual databases; Visual perception;
Conference_Titel :
Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
Conference_Location :
Champaign, IL, USA
Print_ISBN :
0-8186-2855-3
DOI :
10.1109/CVPR.1992.223170