Lesson 1) Introduction and Background [pdf]

Additional resources:
- Video: The Structure From Motion Pipeline (about SFM)
- Video: Bojnický zámok (about image-based dense 3D reconstruction)

Lesson 2) Features Extraction (2D) [pdf]

Additional resources:
- Project web page: ORB-SLAM.

Lesson 3) Features Extraction (3D) [pdf]

Lesson 4) Image-geometry Registration [pdf]

Additional resources:
- Video: Image-geometry registration using MI

Lesson 5) Recent Advances and Applications [pdf]

Additional resources:
- Project web page: Photo Tourism
- Project web page: Photo Cloud
- Project web page: Unstructured Video-Based Rendering: Interactive Exploration of Casually Captured Videos
- Project web page: Videoscapes: Exploring Sparse, Unstructured Video Collections
- Project web page: Painting-to-3D Model Alignment Via Discriminative Visual Elements
- Project web page: Seeing 3D chairs: exemplar part-based 2D-3D alignment using a large dataset of CAD models
- Project web page: CROSSLINK: joint understanding of image and 3D model collections through shape and camera pose variations
- Project web page: Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views

Notes:

- Part of the slides of the first lesson comes from the book "Introduction to Computer Graphics: A Practical Learning Approach".
- Part of the slides of the second lesson comes from the following sources:

- Introduction to Computer Vision by Fei Fei Li, Stanford University.
- CS543 / ECE549: Computer Vision by Svetlana Lazebnik, Dep. of Computer Science, University of Illinois at Urbana-Champaign.
- CS4670 / 5670: Introduction to Computer Vision by Noah Snavely, Computer Science Department, Cornell University.

- Part of the slides of the third lesson comes from the "Polygonal Mesh Processing" book.