A semantics-based decision theory region analyzer
IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
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An Interactive Scene Interpretation System (ISIS) is being developed by Stanford Research Institute's Artificial Intelligence Center as a tool for constructing and experimenting with man-achine and automatic scene analysis methods tailored for particular image domains. A region analysis subsystem was developed recently based on the work of Brice and Fennema, and Yaklmovsky. Using this subsystem a series of experiments was conducted to determine good criteria for initially partitioning a scene into atomic regions and merging these regions into a final partition of the scene along object boundaries. Semantic (problem-dependent) knowledge is essential for complete, correct partitionis of complex real-world scenes. An interactive approach to semantic scene segmentation was developed and demonstrated on both landscape and indoor scenes. This approach provides a reasonable methodology for segmenting scenes that cannot be processed completely automatically at present and Is a promising basis for a future fully automatic system.