A Shape From Shading Analysis for a Single Perspective Image of a Polyhedron
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering Three-Dimensional Shape from a Single Image of Curved Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface Reflection: Physical and Geometrical Perspectives
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape from projected light grid (abstract only)
CSC '87 Proceedings of the 15th annual conference on Computer Science
Using synthetic images to register real images with surface models
Communications of the ACM
Where and Why Local Shading Analysis Works
IEEE Transactions on Pattern Analysis and Machine Intelligence
Radiometric CCD camera calibration and noise estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representation and use of knowledge in vision
ACM SIGART Bulletin
ACM SIGGRAPH 2007 courses
Computer Description of Curved Objects
IEEE Transactions on Computers
A new system to acquire and restore document shape and content
PROCAMS '08 Proceedings of the 5th ACM/IEEE International Workshop on Projector camera systems
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Variable-Source Shading Analysis
International Journal of Computer Vision
Computer Vision and Image Understanding
Shape from single scattering for translucent objects
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Color constancy, intrinsic images, and shape estimation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
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A method will be described for finding the shape of a smooth opaque object from a monocular image, given a knowledge of the surface photometry, the position of the light-source and certain auxiliary information to resolve ambiguities. This method is complementary to the use of stereoscopy which relies on matching up sharp detail and will fail on smooth objects. Until now the image processing of single views has been restricted to objects which can meaningfully be considered two-dimensional or bounded by plane surfaces. It is possible to derive a first-order non-linear partial differential equation in two unknowns relating the intensity at the image points to the shape of the object. This equation can be solved by means of an equivalent set of five ordinary differential equations. A curve traced out by solving this set of equations for one set of starting values is called a characteristic strip. Starting one of these strips from each point on some initial curve will produce the whole solution surface. The initial curves can usually be constructed around so-called singular points. A number of applications of this method will be discussed including one to lunar topography and one to the scanning electron microscope. In both of these cases great simplifications occur in the equations. A note on polyhedra follows and a quantitative theory of facial make-up is touched upon. An implementation of some of these ideas on the PDP-6 computer with its attached image-dissector camera at the Artificial Intelligence Laboratory will be described, and also a nose-recognition program.