On the use of spatial relations between objects for image classification
Date Issued
2007
DOI
10.1007/978-0-387-74161-1_38
Abstract
Image classification is addressed in this paper by utilizing spatial relation of detected objects in a rule-based fashion. Instances of particular object classes are detected combining bottom-up (learn-able models based on simple features) and top-down information(object models consisting of primitive geometric shapes such as lines). The rule-based system acts as a model for the spatial configuration of objects, also providing a human interpretable justification of image classification. Experimental results in the athletic domain show that despite inefficiencies in object detection, spatial relations allow for efficient discrimination between visually similar images classes.
Subjects