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We present a 3D reconstruction system to realize fast 3D modeling using a vision sensor. The system can automatically detect the face region and obtain the depth data as well as color image data once a person appears in front of the sensor. When the user rotates his head around, the system will track the pose and integrate the new data incrementally to obtain a complete model of the personal head quickly. In the system, iterative closest point (ICP) algorithm is first used to track the pose of the head, and then a volumetric integration method is used to fuse all the data obtained. Third, ray casting algorithm extracts the final vertices of the model, and finally marching cubes algorithm generates the polygonal mesh of the reconstructed face model for displaying. During the process, we also make improvements to speed up the system for human face reconstruction. The system is very convenient for real-world applications, since it can run very quickly and be easily operated

Marching Cubes Algorithm for Fast 3D Modeling of Human Face by Incremental Data Fusion