Best Paper: A Novel Augmented Reality Approach in Oral and Maxillofacial Surgery: Super-Imposition Based on Modified Rigid and Non-Rigid Iterative Closest Point
This paper aims to improve the accuracy of super-imposition and processing time during Oral and Maxillofacial surgery. Methodology: The proposed system consists of Enhanced Tracking Learning Detection (TLD) enhance by an occlusion removal algorithm to remove occlusion in the region of interest. In addition, we propose a Modified Rigid and Non-Rigid Iterative Closest Point (MRaNRICP) for pose refinement. Moreover, this proposed MRaNRICP having a new error metric Boolean function to dictate the Iterative Closest Point (ICP)’s stopping condition.