Stereopsis Experiments

Irena Farberov,Andrey Terushkin

StereoThe word "stereo" comes from the Greek

word "stereos" which means firm or solid. With stereo vision you see an object as solid in three spatial dimensions--width, height and depth--or x, y and z. It is the added perception of the depth dimension that makes stereo vision so rich and special.

The person sees world around volume. Therefore quite natural desire is the desire

to embody this world such what it is - having not only width and height, but also depth.

Complexities arise when we will want to see the stereo image removed thus. For this purpose it is necessary, that each eye would see the image intended for it, and did not see the image for other eye. Without special training of an eye at the person look, as a rule, how it is offered to them the nature, instead of the volume image see two flat.

Our Goals

We want to receive the stereo image from two regular pictures

The program should identify three-dimensional subjects

Examining the influence of different factors to received stereo picture.

Finding Correspondences:

Comparing Windows:

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Mostpopular

For each window, match to closest window on epipolar line in other image.

It is closely related to the SSD:

Maximize Cross correlation

Minimize Sum of Squared Differences

Processing Stages•Loading the pictures•Generate disparity map •Generate depth map•Smooth with Gaussian•3D Preview

Examples and results:Simpsons

Examples and results:Result:

Examples and results:Example 2:

Examples and results::

Example3:

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Example3:Results:

Conclusions:The algorithm is very successful on artificial pictures.Success on recognizing shape from random noiseIt is very sensitive to deviation in the epipolar line,

issue that common in real photos.Real photos are never correct :

it is impossible to set the cameras exactly in the same angle

in each camera the objects are differently pushed into pixels

many other problems like color correction on digital cameras.

That fact make real images extremely difficult to recognize.

References:

en.wikipedia.org/wiki/Stereopsis www.vision3d.comwww.lessons4living.com/free.htmhttp://www.knowdotnet.com/articles/examplesandtutoria

l.htmlOhad Ben Shahar, - Lectures on "Introduction to

Computational and Biological Vision", BGU computer science department

Vishvjit S.Nalwa:”A Guided Tour of Computer Vision”Christopher Brown: “Advances in Computer Vision “