Multiple Intensity Differentiation for 3-D Surface Reconstruction With Mono-Vision Infrared Proximity Array Sensor

Abstract

3-D depth sensor technologies, as manifested in several consumers' electronics products, have potential for a technological breakthrough in various application areas such as industrial, medical, and outdoor vision system. Depth sensing of human body motions can promote intuitive gesture inputs for natural HMI (Human Machine Interface) as well as HRI (Human Robot Interaction) to the next level. In today's industry, the dominant trends in 3-D depth sensing are shifting from the traditional laser based scanning or TOF (Time of Flight) depth sensing to the intensity based Infrared 3-D depth mechanism. For example, Microsoft Kinect is a manifestation of such demands for more affordable and real time 3-D depth sensing. In this paper, we investigate currently available 3-D sensor technologies for comparison followed by the presentations of the results in novel mono-vision based 3-D surface sensing and visualization study. The novel method presented in this paper is to calculate the 3-D depth and the surface angle of an object at the same time. The proposed technology is to generate high quality 3-D surfaces with a pure intensity matrix from multiple light sources. The enabling technology is the multiple intensity differentiation method, which is the main focus of study in the paper.