Conceptual and Experimental Vision Introduction R.Bajcsy, S.Sastry and A.Yang Fall 2006.
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Transcript of 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
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
Illusions for Prof. Ramachandran
• http://psy.ucsd.edu/chip/video/Mot_Capt_LQ.rm