PhD thesis - Institute for Computer Graphics and Vision - Graz ...
PhD thesis - Institute for Computer Graphics and Vision - Graz ...
PhD thesis - Institute for Computer Graphics and Vision - Graz ...
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Contents<br />
1 Introduction 1<br />
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1<br />
1.2 Using <strong>Graphics</strong> Processing Units <strong>for</strong> <strong>Computer</strong> <strong>Vision</strong> . . . . . . . . . . . . 2<br />
1.3 3D Models from Multiple Images . . . . . . . . . . . . . . . . . . . . . . . . 5<br />
1.4 Overview of this Thesis <strong>and</strong> Contributions . . . . . . . . . . . . . . . . . . . 10<br />
2 Related Work 15<br />
2.1 Dense Depth <strong>and</strong> Model Estimation . . . . . . . . . . . . . . . . . . . . . . 15<br />
2.1.1 Computational Stereo on Rectified Images . . . . . . . . . . . . . . . 15<br />
2.1.2 Multi-View Depth Estimation . . . . . . . . . . . . . . . . . . . . . . 17<br />
2.1.3 Direct 3D Model Reconstruction . . . . . . . . . . . . . . . . . . . . 18<br />
2.2 GPU-based 3D Model Computation . . . . . . . . . . . . . . . . . . . . . . 19<br />
2.2.1 General Purpose Computations on the GPU . . . . . . . . . . . . . 19<br />
2.2.2 Real-time <strong>and</strong> GPU-Accelerated Dense Reconstruction from Multiple<br />
Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22<br />
3 Mesh-based Stereo Reconstruction Using <strong>Graphics</strong> Hardware 27<br />
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27<br />
3.2 Overview of Our Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28<br />
3.2.1 Image Warping <strong>and</strong> Difference Image Computation . . . . . . . . . . 29<br />
3.2.2 Local Error Summation . . . . . . . . . . . . . . . . . . . . . . . . . 30<br />
3.2.3 Determining the Best Local Modification . . . . . . . . . . . . . . . 31<br />
3.2.4 Hierarchical Matching . . . . . . . . . . . . . . . . . . . . . . . . . . 31<br />
3.3 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33<br />
3.3.1 Mesh Rendering <strong>and</strong> Image Warping . . . . . . . . . . . . . . . . . . 33<br />
3.3.2 Local Error Aggregation . . . . . . . . . . . . . . . . . . . . . . . . . 35<br />
3.3.3 Encoding of Integers in RGB Channels . . . . . . . . . . . . . . . . . 35<br />
3.4 Per<strong>for</strong>mance Enhancements . . . . . . . . . . . . . . . . . . . . . . . . . . . 36<br />
3.4.1 Amortized Difference Image Generation . . . . . . . . . . . . . . . . 36<br />
3.4.2 Parallel Image Trans<strong>for</strong>ms . . . . . . . . . . . . . . . . . . . . . . . . 36<br />
3.4.3 Minimum Determination Using the Depth Test . . . . . . . . . . . . 37<br />
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