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This paper presents a method for 3D surface reconstruction using a deformable model, which integrates fuzzy techniques, deformable model and the level set method. In order to make the result much less sensitive to the initial conditions and noise, fuzzy external forces that drive the model towards surface of object are developed based on a adaptive fuzzy segmentation algorithm. We represent the deformable model as a level set of a 3D scalar function so that the deformable model can reconstruct the 3D surface of the object with complex geometries and topologies. Results of several experiments are shown to demonstrate the effectiveness of our method.

In this paper, a robotic visual servoing based on snakes (or active contours) is presented. The approach uses a combination of active contours with image optical flow for tracking image contours related to the object of interest. The active contours provide global information about the position of the object. When visual servoing is combined with the use of active contours, movement of the camera can be controlled by these information. The proposed method fulfils real-time tracking as well as reliability and robustness requirements. Several experiments were performed to verify the potential of our approach.