Looking to build a model world: automatic construction of static object models using computer vision

Interest in virtual reality and multimedia has provided a great impetus to the development of automatic techniques for building graphical CAD/CAM models of objects and environments by sensing reality itself. The learning of models in this way is essential, particularly in terms of production times and attaining the required high fidelity needed for many applications. Research has produced techniques for extracting full 3D shape models using a variety of sensors and a spectrum of techniques. These include the use of static video cameras, mobile video cameras (e.g. walk through video), multiple camera platforms and/or specialist active range sensors (typically based on laser striping or sonar). This paper introduces the principles and methodologies underlying several of these methods and presents algorithms and examples from systems representative of three major approaches: models from silhouettes, models from active range sensors and, finally, models from passive uncalibrated video sequences