انجمن کامپیوتر ایران

Object tracking is one of the major subjects in machine vision and plays a main role in detection of major events in indoor soccer matches. In this paper, a novel approach for tracking the ball and players is proposed. In this method, the ground lines are segmented and eliminated using a fast and effective method. Then, the remaining non-field pixels are considered and labeled as players and the ball. A fast level set contour is used to track players and the ball. The proposed method can track players and the ball in presence of occlusion. Experiments show that the proposed method is robust to occlusion and different field colors.

In this paper, we introduce a refinement approach to develop probabilistic programs formally. To achieve this goal, we first present a way to specify probabilistic programs in a Z-based notation. We then use an existing method of translating Z into a refinement calculus to transform our Z-style specifications of probabilistic programs into specification statements of the refinement calculus. We finally add new laws to the refinement calculus helping us to refine the resulting specification statements into probabilistic choice constructs of a probabilistic imperative language. In this way, we will provide a completely formal way for developing probabilistic programs.