A Scoring Model of Figural Goodness and Its Application to Contour Completion Problems

This paper models the concept of figural goodness of a shape and apply the model to solving the visual occlusion problem. Based on the observation that 'goodness' of figure is influenced by local and global shape contexts, we model simplicity and regularity of a shape, and define a figural goodness score by linearly combining these two. To evaluate the usefulness and limitation of the proposed scoring, we applying the model to solving a contour completion problem. In the application, various completion paths of occluded contours are generated by a computer using different kinds of completion algorithms. To the generated paths, the best one is selected as the contour completion result by comparing their figural goodness scores. Experimental results have shown that the scoring model of figural goodness works effectively for the contour completion problem.