Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Language and Spatial Cognition
Language and Spatial Cognition
Robot Vision
| Hi-index | 0.00 |
The objective in this paper is to present a framework for a system that describes objects in a qualitative fashion. A subset of spatial prepositions is chosen and an appropriate quantification is applied to each of them that capture their inherent qualitative properties. The quantifications use such object attributes as area, centers, and elongation properties. The familiar zeroth, first, and second order moments are used to characterize these attributes. This paper will detail how and why the particular quantifications were chosen. Since spatial prepositions are by their nature rather vague and dependent on context a technique for fuzzifying the definition of the spatial preposition is explained. Finally an example task is chosen to illustrate the appropriateness of the quantification techniques.