Abstract
The lack of a structured and theoretical approach to reasoning with visual information is a major obstacle for designing and implementing vision systems. The authors provide a four-step methodological approach to this problem: (1) visual reasoning problems are classified into several categories by their characteristics; (2) a particular class of problems, namely two-dimensional object recognition, is examined, and a system model for describing it is formally extracted; (3) several probability-related inference mechanisms are examined, and the one that is most appropriate for reasoning with the above model is chosen; and (4) a hybrid inference mechanism, the outcome of the above comparative study, is applied to a visual reasoning problem. They show how this approach can be used to overcome the difficulties in designing visual reasoning systems. The implications of this work are disussed.
| Original language | English |
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| Title of host publication | Proceedings of the International Workshop on Industrial Applications of Machine Intelligence and Vision |
| Pages | 50-55 |
| Number of pages | 6 |
| Publication status | Published - 1989 |
| Event | International Workshop on Industrial Applications of Machine Intelligence and Vision - Tokyo, Japan Duration: 10 Apr 1989 → 12 Apr 1989 |
Conference
| Conference | International Workshop on Industrial Applications of Machine Intelligence and Vision |
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| City | Tokyo, Japan |
| Period | 10/04/89 → 12/04/89 |