contains material from
Template Matching Techniques in Computer Vision: Theory and Practice
Roberto Brunelli © 2009 John Wiley & Sons, Ltd
A key need in the development of algorithms in computer vision (as in many other fields) is the availability of large data sets for training and testing them. Ideally, data sets should cover the expected variability range of data and be supported by high quality annotations describing what they represent so that the response of an algorithm can be compared to reality. Gathering large, high quality data sets is however a time consuming effort. An alternative is available for computer vision research: computer graphics systems can be used to generate photo-realistic images of complex environments together with supporting ground truth information. This chapter shows how these systems can be exploited to generate a flexible (and cheap) evaluation environment.
keywords: computer graphics, ray tracing, shading language, radiosity, photon mapping, camera simulation.