CS 523 ( CS 423/EE 533) Computer Vision. Lecture 1 INTRODUCTION TO COMPUTER VISION. About the Course. Syllabus. http://vvgl.ozyegin.edu.tr Objective Introduction to the theory, tools, and algorithms of 3D computer vision Instructor Assist. Prof. M. Furkan Kıraç
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CS 523 (CS 423/EE 533)ComputerVision Lecture 1 INTRODUCTION TO COMPUTER VISION
Syllabus http://vvgl.ozyegin.edu.tr Objective Introduction to the theory, tools, and algorithms of 3D computer vision Instructor Assist. Prof. M. Furkan Kıraç E-mail: email@example.com Room: 219 Hours Wednesdays, 10:40-13:30, Room: 241 Grading Projects: 6x10% Final Exam: 40%
Grading • Short Projects:Late submissions are not accepted. Copying answers from others’ work is not permitted. • Final Exam:At least 3 of the 6 Short Projects must be turned in by the due date in order to qualify for the Final Exam. No make-up will be given for the Final Exam. Students can take the Bütünleme exam if they miss the Final Exam.
Recommended Books • Computer Vision: Algorithms and Applications, Richard Szeliski, Springer, 2010. • Computer Vision: A Modern Approach, David A. Forsyth and Jean Ponce, Prentice-Hall, 2002. • Introductory Techniques for 3D Computer Vision, Emanuele Trucco and Alessandro Verri, Prentice-Hall 1998.
OpenCV Resources • Learning OpenCV, Gary Bradski and Adrian Kaehler, O'Reilly, 2008. • OpenCV 2 Computer Vision Application Programming Cookbook, Robert Laganière, Packt Publishing, 2011. • Mastering OpenCV with Practical Computer Vision Projects, Daniel Lélis Baggio, et al., Packt Publishing, 2012.
Topics to be covered • 3D geometry fundamentals • Transformations and projections • Camera calibration • Feature detection and matching • Image stitching • Single view geometry • Two view geometry • Multiple view geometry • Stereo vision and depth estimation • 3D structure from motion • 3D camera tracking
Computer Vision Figure from "Computer Vision: Algorithms and Applications,” Richard Szeliski, Springer, 2010.
Computer Graphics • Lights and materials • Shading • Texture mapping • Environment effects • Animation • 3D scene modeling • 3D character modeling • (OpenGL)
Image Processing Topics • Resampling • Enhancement • Noise filtering • Restoration • Reconstruction • Segmentation • Image compression • (MATLAB and OpenCV)
Video Processing Topics • Spatio-temporal sampling • Motion estimation • Frame-rate conversion • Multi-frame noise filtering • Multi-frame restoration • Super-resolution • Video compression • (MATLAB & OpenCV)
Video acquisition-display chain Capture Representation Coding Transmission Decoding Rendering
Rods vs. Cones • Rods • Perceive brightness only • Night vision • Cones • Perceive color • Day vision • Red, green, and blue cones
Cone Distribution Blue is less-focused 64% 32% 2%
Spatial Resolution of the Human Eye • Photopic (bright-light) vision: • Approximately7 millioncones • Concentratedaround fovea • Scotopic (dim-light) vision • Approximately75-150 millionrods • Distributed over retina (HDTV: 1920x1080 = 2 millionpixels)