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A points surface reconstruction algorithm of 3D object models from multiple silhouettes is proposed in this paper. Some images of the target object are taken from a circular trajectory by a robot with a camera mounted in an eye-in-hand configuration. The silhouettes of the observed object are evaluated for each view using a blob analysis process, and from those a set of points that sample a reconstruction sphere surrounding the target object are estimated. The sphere sample points are attracted by the object center of mass using a variable step according to the distance from the silhouettes contours. For each point, the iterative process of constriction is stopped when all the back-projections of the point are within the corresponding silhouettes. Moreover, a new method based on a rough estimation of object dimension is proposed to reduce the disturbances due to projection and shadow cones. Simulations and experiments are presented to evaluate the performance of the proposed algorithm.