Understanding how the shape of a three dimensional object may be recovered from shading in a two-dimensional image of the object is one of the most important - and still unresolved - problems in machine vision. Although this important subfield is now in its second decade, this book is the first to provide a comprehensive review of shape from shading. It brings together all of the seminal papers on the subject, shows how recent work relates to more traditional approaches, and provides a comprehensive annotated bibliography.The book's 17 chapters cover: Surface Descriptions from Stereo and Shading. and Source from Shading. The Eikonal Equation: some Results Applicable to Computer Vision. A Method for Enforcing Integrability in from Algorithms. Obtaining from Information. The Variational Approach to from Shading. Calculating the Reflectance Map. Numerical from and Occluding Boundaries. Photometric Invariants Related to Solid Shape. Improved Methods of Estimating from Using the Light Source Coordinate System. A Provably Convergent Algorithm for from Shading. Recovering Three Dimensional from a Single Image of Curved Objects. Perception of Solid from Shading. Local Analysis Pentland. Radarclinometry for the Venus Radar Mapper. Photometric Method for Determining Surface Orientation from Multiple Images.Berthold K. P. Horn is Professor of Electrical Engineering and Computer Science at MIT. He has presided over the field of machine vision for more than a decade and is the author of Robot Vision. Brooks is Reader in Computer Science at The Flinders University of South Australia. Shape from Shading is included in the Artificial Intelligence series, edited by Michael Brady, Daniel Bobrow, and Randall Davis.
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