What ’ s in an Image ? Towards the Computation of the “ Best ” View of an Object

There are many possible 2D views of a given 3D object and most people would agree that some views are more aesthetic and/or more “informative” than others. Thus, it would be very useful, in many applications, to be able to automatically compute these “best” views. Although all measures of the quality of a view will ultimately be subjective, hence difficult to quantify, we propose some general principles which may be used to address this challenge. In particular, we describe a number of different ways to measure the goodness of a view, and show how to optimize these measures by reducing the size of the search space.

[1]  R. Weale Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr , 1983 .

[2]  I. Biederman Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.

[3]  Anil K. Shukla Mathematics of aesthetics , 1987 .

[4]  Satoru Kawai,et al.  A simple method for computing general position in displaying three-dimensional objects , 1988, Comput. Vis. Graph. Image Process..

[5]  H H Bülthoff,et al.  How are three-dimensional objects represented in the brain? , 1994, Cerebral cortex.

[6]  Michael Werman,et al.  On View Likelihood and Stability , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  A. David Marshall,et al.  Viewpoint Selection for Complete Surface Coverage of Three Dimensional Objects , 1998, BMVC.

[8]  Jesse Freeman,et al.  in Morse theory, , 1999 .

[9]  M J Tarr,et al.  What Object Attributes Determine Canonical Views? , 1999, Perception.

[10]  Frank P. Ferrie,et al.  Viewpoint selection by navigation through entropy maps , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[11]  Dimitri Plemenos,et al.  Scene understanding techniques using a virtual camera , 2000, Eurographics.

[12]  Michael Elad,et al.  Directed Search In A 3D Objects Database Using SVM , 2000 .

[13]  Erik Reinhard,et al.  Artistic Composition for Image Creation , 2001, Rendering Techniques.

[14]  Godfried T. Toussaint,et al.  Nice Perspective Projections , 2001, J. Vis. Commun. Image Represent..

[15]  Mateu Sbert,et al.  Viewpoint Selection using Viewpoint Entropy , 2001, VMV.

[16]  Michael J Tarr,et al.  What defines a view? , 2001, Vision Research.

[17]  Wolfgang Straßer,et al.  A case study on automatic camera placement and motion for visualizing historical data , 2002, IEEE Visualization, 2002. VIS 2002..

[18]  Michael Elad,et al.  Content based retrieval of VRML objects: an iterative and interactive approach , 2002 .

[19]  Mongi A. Abidi,et al.  Shape analysis algorithm based on information theory , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[20]  Tamal K. Dey,et al.  Shape Segmentation and Matching with Flow Discretization , 2003, WADS.

[21]  J. Koenderink,et al.  The internal representation of solid shape with respect to vision , 1979, Biological Cybernetics.

[22]  David W. Jacobs,et al.  Mesh saliency , 2005, SIGGRAPH 2005.