scholarly journals Three-dimensional object shape from shading and contour disparities

2008 ◽  
Vol 8 (11) ◽  
pp. 11-11 ◽  
Author(s):  
H. T. Nefs
Keyword(s):  
Three Dimensional ◽  
Shape From Shading ◽  
Object Shape ◽  
Dimensional Object

scholarly journals A neural code for three-dimensional object shape in macaque inferotemporal cortex

2008 ◽  
Vol 11 (11) ◽  
pp. 1352-1360 ◽  
Author(s):  
Yukako Yamane ◽  
Eric T Carlson ◽  
Katherine C Bowman ◽  
Zhihong Wang ◽  
Charles E Connor
Keyword(s):  
Three Dimensional ◽  
Neural Code ◽  
Inferotemporal Cortex ◽  
Object Shape ◽  
Dimensional Object

Statistical Approach to Shape from Shading: Reconstruction of Three-Dimensional Face Surfaces from Single Two-Dimensional Images

1996 ◽  
Vol 8 (6) ◽  
pp. 1321-1340 ◽  
Author(s):  
Joseph J. Atick ◽  
Paul A. Griffin ◽  
A. Norman Redlich
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Practical Interest ◽  
Principal Component ◽  
Shape From Shading ◽  
Shape Space ◽  
Two Dimensional ◽  
Two Dimensional Image ◽  
Low Dimensional ◽  
Dimensional Object

The human visual system is proficient in perceiving three-dimensional shape from the shading patterns in a two-dimensional image. How it does this is not well understood and continues to be a question of fundamental and practical interest. In this paper we present a new quantitative approach to shape-from-shading that may provide some answers. We suggest that the brain, through evolution or prior experience, has discovered that objects can be classified into lower-dimensional object-classes as to their shape. Extraction of shape from shading is then equivalent to the much simpler problem of parameter estimation in a low-dimensional space. We carry out this proposal for an important class of three-dimensional (3D) objects: human heads. From an ensemble of several hundred laser-scanned 3D heads, we use principal component analysis to derive a low-dimensional parameterization of head shape space. An algorithm for solving shape-from-shading using this representation is presented. It works well even on real images where it is able to recover the 3D surface for a given person, maintaining facial detail and identity, from a single 2D image of his face. This algorithm has applications in face recognition and animation.

Analysis technique for the measurement of a three-dimensional object shape

1993 ◽  
Vol 32 (5) ◽  
pp. 737 ◽  
Author(s):  
Pingfan Wu ◽  
Feihong Yu ◽  
Zhengmin Li ◽  
Zhongjun Yan ◽  
Yangyuan Shun
Keyword(s):  
Three Dimensional ◽  
Object Shape ◽  
Analysis Technique ◽  
Dimensional Object

KNOWLEDGE-BASED SHAPE-FROM-SHADING

1999 ◽  
Vol 13 (01) ◽  
pp. 1-23 ◽  
Author(s):  
NICK BARNES ◽  
ZHI-QIANG LIU
Keyword(s):  
Domain Knowledge ◽  
Three Dimensional ◽  
Shape From Shading ◽  
Basic Operation ◽  
Early Vision ◽  
New Paradigm ◽  
Generic Properties ◽  
Knowledge Based ◽  
Edge Matching ◽  
Dimensional Object

In this paper, we study the problem of recovering approximate shape from the shading of a three-dimensional object in a single image when knowledge about the object is available. The application of knowledge-based methods to low-level image processing tasks will help overcome problems that arise from processing images using a pixel-based approach. Shape-from-shading has generally been approached by precognitive vision methods where a standard operator is applied to the image based on assumptions about the imaging process and generic properties of what appears. This paper explores some advantages of applying knowledge and hypotheses about what appears in the image. The knowledge and hypotheses used here come from domain knowledge and edge-matching. Specifically, we are able to find solutions to some problems that cannot be solved by other methods and gain advantages in terms of computation speed over similar approaches. Further, we can fully automate the derivation of the approximate shape of an object. This paper demonstrates the efficacy of using knowledge in the basic operation of an early vision operator, and so introduces a new paradigm for computer vision that may be applied to other early vision operators.

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