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Introduction

Introduction. CSc 83300 Spring 2006 Reading in 3D Computer Vision and Video Computing. Instructor: Zhigang Zhu zzhu@ccny.cuny.edu. Lecture 1: Introduction. http://www-cs.engr.ccny.cuny.edu/~zhu/GC-Spring2006/CSc83300-Video-Computing-2006.html. C. C V C L. Research at CcvcL.

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Introduction

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  1. Introduction CSc 83300 Spring 2006 Reading in 3D Computer Vision and Video Computing Instructor: Zhigang Zhu zzhu@ccny.cuny.edu Lecture 1: Introduction http://www-cs.engr.ccny.cuny.edu/~zhu/GC-Spring2006/CSc83300-Video-Computing-2006.html

  2. C CVC L Research at CcvcL • Research Projects at • The City College Visual Computing Lab • 3D video mosaicing, representation and rendering • Multimodal human signature detection • Robotized Sensor networks • 3D cargo and vehicle inspection • The NSF PI Meeting Talk • The UTRC Hi-Tech Meeting Talk http://www-cs.engr.ccny.cuny.edu/~zhu/research.html

  3. Purpose-Driven Reading • A slightly new approach: purpose-driven reading • Goals come first • Readings come second • Projects come last • Some more details • Get to know what you want to do • Figure out potential projects and the goals • Find related papers to read and present • Try out something new and/or interesting • Write out something • Ideally publications for a conference or journal

  4. Homework # 1 • Submit your resume with • Education (where/what/how good) • Skills (what you are good at: GUI, algorithm, hardware) • Work Experiences ( R&D) • Publications (if any) • Projects related to imaging, vision and graphics (IVG) • Your advisors (if any) • Courses taken • Particularly math, CS, EE related to IVG • Algorithms, Signal processing, etc

  5. Course Organization • Lectures by me (4 lectures) • Basics in 3D computer vision • Camera models, calibration, stereo, motion • Talks by others • CCNY lecture series, GC CS Colloquium • Project Ideas by us • 3D vision, video and robotics • Some ongoing work at the CCNY Visual Computing Lab • Your research interests (2nd level up) • Presentations by you ( ~ 3 times each, 2 – 3 each class meet) • Others’ work (1~2) • Your work proposals and work reports (1~2) • Office Hours • Tuesday 4:30 – 6:00 pm

  6. Course Web Page http://www-cs.engr.ccny.cuny.edu/~zhu/GC-Spring2006/CSc83300-Video-Computing-2006.html • Lectures available in Powerpoint format • Reading schedule will be posted on the web • All assignments will be distributed over the web • Additional materials and pointers to other web sites March 6-10: A talk by Prof. Harvey Rhody @ RIT Monday or Tuesday ?

  7. Book • Textbook • “Introductory Techniques for 3-D Computer Vision” Trucco and Verri, 1998 • Additional readings when necessary • “Computer Vision – A Modern Approach” Forsyth and Ponce, 2003 • “Three-Dimensional Computer Vision: A Geometric Viewpoint” O. Faugeras, 1998 • On-Line References and Reading Materials

  8. C++ and Matlab • C++ • For some simple computation, you may use C++ • Matlab • An interactive environment for numerical computation • Available on Computer Labs machines (both Unix and Windows) • Matlab primer available on line (web page) • Pointers to on-line manuals also available • Good rapid prototyping environment • You should use C++ and/or Matlab for your homework assignments and project(s); Java will also be fine

  9. Grading • Homework (about 2~3): 20% • Course Work: 40% • Reading – Related work by others • Experiments – Results by yourselves • Written Report – Papers or TRs • Presentations (2~3 per student): 40%

  10. 3D Computer Vision • What makes (3D) Computer Vision interesting ? • Image Modeling/Analysis/Interpretation • Interpretation is an Artificial Intelligence Problem • Sources of Knowledge in Vision • Levels of Abstraction • Interpretation often goes from 2D images to 3D structures • since we live in a 3D world • Image Rendering/Synthesis/Composition • Image Rendering is a Computer Graphics problem • Rendering is from 3D model to 2D images 2D images CG CV 3D world

  11. IP vs CV • Image processing (mainly in 2D) • Image to Image transformations • Image to Description transformations • Image Analysis - extracting quantitative information from images: • Size of a tumor • distance between objects • facial expression • Image restoration. Try to undo damage • needs a model of how the damage was made • Image enhancement. Try to improve the quality of an image • Image compression. How to convey the most amount of information with the least amount of data

  12. Video Computing • Some Examples on Video Computing • Video compression • Video surveillance • Video manipulation (video texture, video composition) • Video mosaicing • Video segmentation • 3D video

  13. Approaches general • Three interesting approaches: • Computational Vision: Image Structure • David Marr (MIT) • Knowledge-Based Vision: Image Structure • Active Vision • Applied Vision Images Function(Control) • many others • Different methodological assumptions • Different methods • Different results • Where is Video Computing? • an example.... draw your own conclusions! specific

  14. Related Fields All three are interrelated! • Image Processing: image to image • Computer Vision:Image to model • Computer Graphics: model to image • Pattern Recognition: image to class • image data mining/ video mining • Artificial Intelligence: machine smarts • Machine perception • Photogrammetry: camera geometry, 3D reconstruction • Medical Imaging: CAT, MRI, 3D reconstruction (2nd meaning) • Video Coding: encoding/decoding, compression, transmission • Physics & Mathematics: basics • Neuroscience: wetware to concept • Computer Science: programming tools and skills? AI Applications basics

  15. Applications • Visual Inspection (*) • Robotics (*) • Intelligent Image Tools • Image Compression (MPEG 1/2/4/7) • Document Analysis (OCR) • Image Libraries (DL) • Virtual Environment Construction (*) • Environment (*) • Media and Entertainment • Medicine • Astronomy • Law Enforcement (*) • surveillance, security • Traffic and Transportation (*) • Tele-Conferencing and e-Learning (*)

  16. Job Markets • Homeland Security • Port security – cargo inspection, human ID, biometrics • Facility security – Embassy, Power plant, bank • Surveillance – military or civil • Media Production • Cartoon / movie/ TVs/ photography • Multimedia communication, video conferencing • Research in image, vision, graphics, virtual reality • 2D image processing • 3D modeling, virtual walk-through • Consumer/ Medical Industries • Video cameras, Camcorders, Video phone • Medical imaging 2D -> 3D

  17. C CVC L Research at CcvcL • Research Projects at • The City College Visual Computing Lab • 3D video mosaicing, representation and rendering • Multimodal human signature detection • Robotized Sensor networks • 3D cargo and vehicle inspection • The NSF PI Meeting Talk • The UTRC Hi-Tech Meeting Talk http://www-cs.engr.ccny.cuny.edu/~zhu/research.html

  18. C CVC L Research at CcvcL • Research Projects at • The City College Visual Computing Lab • 3D video mosaicing, representation and rendering • Multimodal human signature detection • Robotized Sensor networks • 3D cargo and vehicle inspection • The NSF PI Meeting Talk • The UTRC Hi-Tech Meeting Talk http://www-cs.engr.ccny.cuny.edu/~zhu/research.html

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