Depth Mapping Algorithm Performance Analysis: Difference between revisions

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You can include images as follows (you will need to upload the image first using the toolbox on the left bar.):  
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[[File:Screen_Shot_2016-11-29_at_7.05.37_PM.png|200px]]
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Revision as of 01:57, 15 December 2017

Introduction

We will implement various disparity estimation algorithms and compare their performance.

Background

Disparity Maps

Depth information about a scene can be captured using a stereo camera (2 cameras that are separated horizontally but aligned vertically). The stereo image pair taken by the stereo camera contains this depth information in the horizontal differences that can be seen in the

Stereo image pair → rectification to preserve only horizontal differences.

Use these differences to determine if objects are closer or farther.

How to get these differences (disparities)?

Figure 1


Relationship Between Disparity and Depth

Disparity and depth can be related by the following equation (where x-x' is disparity, z is depth, f is the focal length, and B is the interocular distance).

xx=Bfz

Methods

Results

Conclusions

Appendix

You can write math equations as follows: y=x+5

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