An important task in computer vision is to recover 3D information of the world around us. A 3D time-of-flight (TOF) camera is one specific emerging technology developed for 3D measurement and is now extensively used in areas such as robotics, automotive and security. The purpose of this book is to develop an important understanding of the measurement processes of 3D TOF cameras and to exploit the potential of 3D image technology in computer vision applications. An important step prior to developing high performance TOF camera applications is the formulation of a detailed and accurate statistical model of the measurements. In this work, a robust framework of signal-to-noise ratio is developed that provides an in-depth information of range estimation in these cameras. The process of 3D TOF camera measurement is understood by examining the reflectance modelling of objects to develop a unified radiometric model for TOF camera. Applications related to smart automotive industry by developing a four dimensional obstacle detection algorithm is also presented. Throughout this work, real and simulated data is used for empirical analysis and verification of applications and algorithms.