3-D Time-Varying Scene Capture Technologies—A Survey

Abstract

Advances in image sensors and evolution of digital computation is a strong stimulus for development and implementation of sophisticated methods for capturing, processing and analysis of 3D data from dynamic scenes. Research on perspective time-varying 3D scene capture technologies is important for the upcoming 3DTV displays. Methods such as shape-from-texture, shape-from-shading, shape-from-focus, and shape-from-motion extraction can restore 3D shape information from a single camera data. The existing techniques for 3D extraction from single-camera video sequences are especially useful for conversion of the already available vast mono-view content to the 3DTV systems. Scene-oriented single-camera methods such as human face reconstruction and facial motion analysis, body modeling and body motion tracking, and motion recognition solve efficiently a variety of tasks. 3D multicamera dynamic acquisition and reconstruction, their hardware specifics including calibration and synchronization and software demands form another area of intensive research. Different classes of multiview stereo algorithms such as those based on cost function computing and optimization, fusing of multiple views, and feature-point reconstruction are possible candidates for dynamic 3D reconstruction. High-resolution digital holography and pattern projection techniques such as coded light or fringe projection for real-time extraction of 3D object positions and color information could manifest themselves as an alternative to traditional camera-based methods. Apart from all of these approaches, there also are some active imaging devices capable of 3D extraction such as the 3D time-of-flight camera, which provides 3D image data of its environment by means of a modulated infrared light source.