Point clouds have been used as a new data structure for 3D models in the fields of 3D computer graphics and computer-aided design. In this study, we propose a method for extracting the features from a point cloud based on the salience of a shape (as a basic research). The proposed method can be applied for shape analysis, recognition, similarity retrieval, and so on. This method extracts the features from a point cloud without constructing a polygonal mesh. First, the method calculates a variance vector using the differences between the normal vectors of each point. Next, using the distance and variance values, the feature is computed as the Y-intercept of linear regression. Several experimental results show that the method is effective for extracting the features from point clouds.

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This paper focuses on distributed LED lighting systems composed of multiple LED lights, and addresses the lighting pattern design problem for the systems. In the design problem, the dynamic lighting, which is PWM type lighting, is considered, and the lighting patterns are determined such that a supplying illuminance distribution is similar to a desired one. In this paper, we first propose a distributed optimization algorithm for determining lighting patterns. Then, we develop an experimental equipment with 25 LED units. Finally, we verify the effectiveness of our algorithm and the fault-tolerance of the distributed lighting system through some control experiments.

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