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Computer Vision (CSE 576) Staff Today Intros Computer vision overview Course overview Image processing Steve Seitz Rick Szeliski TA: Jiun-Hung Chen
Computer Vision (CSE 576) Staff Today Intros Computer vision overview Course overview Image processing Steve Seitz Rick Szeliski TA: Jiun-Hung Chen Web Page Handouts signup sheet intro slides image filtering slides Readings Book: Richard Szeliski, Computer Vision: Algorithms and Applications (please check Web site weekly for updated drafts) Intro: Ch 1.0 What is computer vision? What is computer vision? Terminator 2 1 Every picture tells a story Can computers match (or beat) human vision? Goal of computer vision is to write computer programs that can interpret images Yes and no (but mostly no!) humans are much better at hard things computers can be better at easy things Human perception has its shortcomings Sinha and Poggio, Nature, 1996 Copyright A.Kitaoka Current state of the art The next slides show some examples of what current vision systems can do Earth viewers (3D modeling) Image from Microsoft s Virtual Earth (see also: Google Earth) Photosynth Optical character recognition (OCR) Technology to convert scanned docs to text If you have a scanner, it probably came with OCR software Based on Photo Tourism technology developed here in CSE! by Noah Snavely, Steve Seitz, and Rick Szeliski Digit recognition, AT&T labs License plate readers 3 Face detection Smile detection? Many new digital cameras now detect faces Canon, Sony, Fuji, Sony Cyber-shot T70 Digital Still Camera Object recognition (in supermarkets) Face recognition LaneHawk by EvolutionRobotics A smart camera is flush-mounted in the checkout lane, continuously watching for items. When an item is detected and recognized, the cashier verifies the quantity of items that were found under the basket, and continues to close the transaction. The item can remain under the basket, and with LaneHawk,you are assured to get paid for it Who is she? 4 Vision-based biometrics Login without a password How the Afghan Girl was Identified by Her Iris Patterns Read the story Fingerprint scanners on many new laptops, other devices Face recognition systems now beginning to appear more widely Object recognition (in mobile phones) Special effects: shape capture This is becoming real: Microsoft Research Point & Find, Nokia The Matrix movies, ESC Entertainment, XYZRGB, NRC 5 Special effects: motion capture Sports Sportvision first down line Nice explanation on Pirates of the Carribean, Industrial Light and Magic Click here for interactive demo Smart cars Slide content courtesy of Amnon Shashua Vision-based interaction (and games) Digimask: put your face on a 3D avatar. Mobileye Vision systems currently in high-end BMW, GM, Volvo models By 2010: 70% of car manufacturers. Video demo Nintendo Wii has camera-based IR tracking built in. See Lee s work at CMU on clever tricks on using it to create a multi-touch display! Game turns moviegoers into Human Joysticks, CNET Camera tracking a crowd, based on this work. 6 Vision in space Robotics NASA'S Mars Exploration Rover Spirit captured this westward view from atop a low plateau where Spirit spent the closing months of Vision systems (JPL) used for several tasks Panorama stitching 3D terrain modeling Obstacle detection, position tracking For more, read Computer Vision on Mars by Matthies et al. NASA s Mars Spirit Rover Medical imaging Current state of the art You just saw examples of current systems. Many of these are less than 5 years old This is a very active research area, and rapidly changing Many new apps in the next 5 years To learn more about vision applications and companies David Lowe maintains an excellent overview of vision companies 3D imaging MRI, CT Image guided surgery Grimson et al., MIT 7 This course Project 1: features Project 2: panorama stitching Project 3: Face Recognition Indri Atmosukarto, sp 8 Final Project Open-ended project of your choosing (in teams of two) Grading Based on projects No midterm or final General Comments Prerequisites these are essential! Data structures A good working knowledge of C and C++ programming (or willingness/time to pick it up quickly!) Linear algebra Vector calculus Course does not assume prior imaging experience computer vision, image processing, graphics, etc. 9
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