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.
|Title of host publication||Proceedings of the International Workshop on Industrial Applications of Machine Intelligence and Vision|
|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||International Workshop on Industrial Applications of Machine Intelligence and Vision|
|Period||10/04/89 → 12/04/89|