Camera Modeling for 3D Sensing Using Fuzzy Modeling Concept Based on Stereo Vision

Abstract

Recently, the three-dimensional (3D) sensing technique that uses multiple cameras has been applied to various areas, such as visualization, motion capturing, and so on. However, improvement of camera model calibration is required for higher precision of measurements. In this study, we propose a practicable fuzzy modeling approach for 3D sensing that utilizes stereo vision configuration. The distance between a sensing target and the camera is used to construct a camera fuzzy model that considers optical projection characteristics. In our approach, the weighted least squares method is successfully applied considering a fuzzy partition to formulate the fuzzy model. Then, iterative calculations for solving the inverse problem of the camera fuzzy model are performed to obtain measured coordinates. Through sensing experiments of stereo vision measurement based on the proposed approach, we show that performance of the model is drastically improved compared with the conventional modeling approach.