Advances in 3D Reconstruction Techniques: From Stereo Matching to Camera Calibration
This compilation reviews key advancements in 3D reconstruction, covering various approaches like spectral partitioning, multi-baseline stereo, and dense matching. Highlights include shape from motion, depth estimation techniques, and the fundamentals of camera calibration. Noteworthy works by researchers such as Nelson Drew Steedly and Eric Wong discuss methods such as depth from defocusing and space carving. The collection also addresses augmented reality applications, feature tracking, and view synthesis from image sequences, showcasing the evolution and diversity of techniques in 3D imaging.
Advances in 3D Reconstruction Techniques: From Stereo Matching to Camera Calibration
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Presentation Transcript
ELE 5450 Projects • 3D Reconstruction • 1. Spectral partition for structure from motion Nelson Drew Steedly et al p. 996 ICCV 2003 • 2. Multi-baselines stereo for 3D reconstruction Xie Jun • 3. Dense stereo matching • 4. Shape from motion using an orthographic camera Ann Lee
3D reconstruction • 5. Depth from motion • 6. Stereo Space Wang Xiaona • Seitz ICCV 2001 • 7. Depth from defocusing Eric • 8. A theory of shape by space carving Harry Ng • Kutulakos and Seitz IJCV 38(3) 197-216, 2000
Camera calibration • Camera calibration using three squares Tang YM • Camera self calibration from an image sequence captured by a handheld camera Qin Chao • Camera calibration for estimating radial distortion • Computation of the fundamental matrix F
Augmented Reality and Mosaics Wang Xiaona • 1. Concentric mosaics • 2. Feature tracking for virtual reality • 3. Stereo panoramas Chan Ya Wen • 4 View Synthesis form images of two view points
