Conceptual and Experimental Vision Introduction R.Bajcsy, S.Sastry and A.Yang Fall 2006

Introduction and plan for the course We plan to follow the text :An Invitation to 3-D Vision by Yi Ma, Stefano Soatto,Jana Kosecka and S.S.Sastry. Plus some additional papers on real time, Active Vision. Approximately every two weeks there will be a problem set and programming homework assignment There will no midterm and final, but projects instead. Students are expected to participate in the class.

The proposed Syllabus Week 1: Introduction Week 2: Image formation : geometry, optics, Radiometry and error analysis Week 3: Image primitives and correspondence Week 4: Review of basic algebra and geometry Week 5 :Epipolar geometry Week 6: Camera calibration Week 7: Structure from motion Week 8: Optimization

Syllabus cont., Week 9: Real Time Vision Week 10: Visual feedback Week 11: Active Vision Week 12: Introduction to GPCA: Iterative methods Week 13: Introduction to GPCA:Algebraic Methods Week 14: Estimation and Segmentation of Hybrid Models, and Applications Week 15:Projects

Our expectation Through this course, students should acquire the ability to study computer vision through rigorous mathematical frameworks. By the end of the course, students should be familiar with the history of computer vision, the start-of-the-art performance of current vision systems, and important open problems in the literature. Experimentally, students should be able to setup a stereo camera system, evaluate its characteristics, calibrate it, and reconstruct motions of single and multiple objects.

What is Vision? From the 3-D world to 2-D images: image formation (physics). Domain of artistic reproduction (synthesis): painting, graphics. From 2-D images to the 3-D world: image analysis and reconstruction (mathematical modeling, inference). Domain of vision: biological (eye and brain) computational

Topics from a vision conf.: CVPR06

CVPR 2006 cont.

What we will cover Geometry Stereo and 3D reconstruction Matching and Registration Segmentation Real time considerations Visual feedback and control Error analysis of the sensor system

What we will not cover Recognition Learning Tracking and video analysis Low level analysis an graphics and Image Synthesis

Our Brain

Our eye vs. Camera

Multiple views

Camera’s multiple views

Illusions

Illusions for Prof. Ramachandran

What painters knew

Perspective Imaging and other monocular cues

Image Analysis

3-D Modeling and Rendering

Image Mosaicing and panoramic views

3-D reconstruction

3-D data acquisition and reconstruction

Geometry and Photometry

Compare recovered shape and laser scanned object

Data Acquisition and integration of Indian Baskets

Real Time Virtual Object Insertion

UAV at Berkeley

Vision based driving

Tele-Immersive environment for Communication