An ongoing effort is being made in the field of computer vision to refine algorithms for optimal/better performance, which can mean reliability and increased computational speed. This is highly important given that vision problems are much larger than ever before. One way to satisfy part of the demand is to design more efficient and clever algorithms that optimize computations in an existing processor, rather than require expanded processor performance. Such fast algorithms are becoming increasingly important for tele-reality, interactive media and visual serving applications. This book presents some fast and reliable algorithms for dense stereo matching and optical-flow estimations using a general language, such as C, rather than dedicated hardware implementation. "Dense" in this instance means performing stereo matching for every point on the image rather than just matching features such as points, lines or regions. Techniques described are: fast algorithms for similarity measure, use of subregioning technique to expedite similarity calculation, multiresolution scheme, fast 3-D surface technique for stereo matching, and stereo matching using warping. Fast Algorithms for Stereo Matching is useful for academics, professionals, researchers, practitioners, and advanced graduate students in the areas of computer vision, digital photogrammetry, and 3-D video coding.