APPLICATION OF SURFACE CONSTRAINT FOR MODELING THE STEREOPSIS OF UNTEXTURED STEREOGRAMS
((János Geier)) Eötvös Loránd University, Budapest, Hungary.
Purpose
I present a computational model and a computer algorithm for the stereo depth problem for both textured and untextured stereograms. (This is a modified version of the model I presented last year ARVO95 #1322). A new constraint has been developed to avoid false targets and to solve the problem related to half-occluded regions.
____________________________________
Supported by MAKA, (US-Hungarian Joint Fund) J.F. No. 360
The main question:
Which 3D surface is the one that is in the best correspondence with the given stereo image pair?
The answer is based on the
surface constraint:
Take a stereo image pair with known camera-parameters, and project the left and right images back onto the original 3D object in its original position, then the projected images will perfectly overlap on the surface of the object, except in the half-occluded regions.
The computational goal is to find a representation of the 3D surface that provides the best fulfillment of the surface constraint.
How can we measure the best overlap (i.e. the best fulfilling)?
Suppose the 3D surface is represented in the computer program by a
grid with size nx*ny, where for all (x,y) gridpoints the z value of depth is given:grid={ xi,yj,zij; i=1..nx, j=1..ny}
The measure for the overlap on a given 3D surface is defined by the following value:
where
L(.,.) and R(.,.) is the intensity distribution on the left and right image respectively, and
point to the left retina, and
point to the right retina.
The computational goal in computer terms is to find the
grid that results in the minimal Q(grid) value.The computer algorithm has been tested on real life images, on computer generated random dot stereograms and on simple untextured stereograms.
Results
Conclusions
