In order to reconstruct a surface by using the data from RGB-D sensor, this paper presents a viewpoint based method for estimating the orientation of point clouds. Firstly, a PCA method is used to compute the normal vector of each point. In this process, the orientation of the normal is determined by the viewpoint. Secondly, the point clouds generated from each frame are combined to an overall model with directional information. Finally, the quality of the model is further improved by a local smooth method. The experimental results show that the method can compute accurate normal vectors on the fly. Compared to current methods, it can estimate the sign of the normal automatically.
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