Shape from Shading: A Method for Obtaining the Shape of a Smooth Opaque Object from One View

Item

Title
en_US Shape from Shading: A Method for Obtaining the Shape of a Smooth Opaque Object from One View
Creator
en_US Horn, Berthold K.P.
Date
2004-10-20T20:04:25Z
Date Available
2004-10-20T20:04:25Z
Date Issued
en_US 1970-11-01
Identifier
en_US AITR-232
uri
http://hdl.handle.net/1721.1/6885
Abstract
en_US A method will be described for finding the shape of a smooth apaque object form a monocular image, given a knowledge of the surface photometry, the position of the lightsource 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 objects. 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 metod 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.
Extent
8653278 bytes
6781058 bytes
Format
application/pdf
application/postscript
Language
en_US
Relation
en_US AITR-232
Item sets
AI Technical Reports (1964 - 2004)