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  1. szeliski.org › BookComputer Vision: Algorithms and Applications, 2nd ed.

    This book is largely based on the computer vision courses that I have co-taught at the University of Washington (2020, 2008, 2005, 2001) with Steve Seitz and Harpreet Sawhney and at Stanford (2003) with David Fleet.

  2. mitp-content-server.mit.edu › 14500 › tocFoundations of Computer Vision

    Contents Preface ...

  3. vision.stanford.edu › lecture1_introduction_cs231aLecture 1: Introduction to “Computer Vision”

    • Today’s agenda
    • Biology Psychology
    • • To bridge the gap between pixels and “meaning”
    • vision?
    • Change blindess
    • What is (computer) vision?
    • Vision as a source of semantic information
    • Why study computer vision?
    • Why study computer vision?
    • Challenges: illumination
    • Magritte, 1957
    • Challenges or opportunities?
    • Face detection
    • Biometrics
    • • If you have a scanner, it probably came with OCR software
    • LaneHawk by EvolutionRobotics
    • The computer vision industry
    • GeneratedCaptionsTabForHeroSec

    Introduction to computer vision Course overview Quiz?

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    Neuroscience Robotics Cognitive sciences graphics,algorithms, system,theory,... Speech Computer Vision Information retrieval Image processing Machine learning Physics Maths Computer Science

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    What we see What a computer sees What is (computer)

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    Image (or video) Sensing device Interpreting device Interpretations garden, spring, bridge, water, trees, flower, green, etc.

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    Rensink, O’regan, Simon, etc. Change blindess Rensink, O’regan, Simon, etc. segmentation

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    Image (or video) Interpretations garden, spring, bridge, water, trees, flower, green, etc.

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    amusement park sky The Wicked Twister ride Lake Erie water tree deck tree Ferris wheel Cedar Point ride tree

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    • Vision is useful: Images and video are everywhere! photo Movies, news, sports Surveillance and security Medical and scientific images

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    Vision is useful Vision is interesting Vision is difficult Half of primate cerebral cortex is devoted to visual processing Achieving human-level visual perception is probably “AI-complete”

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    image credit: J. Koenderink Challenges: scale Challenges: deformation

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    slide credit: Fei-Fei, Fergus & Torralba Challenges: background clutter Challenges: Motion

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    Images are confusing, but they also reveal the structure of the world through numerous cues Our job is to interpret the cues! Depth cues: Linear perspective Depth cues: Aerial perspective Depth ordering cues: Occlusion Shape cues: Texture gradient Shape and lighting cues: Shading Position and lighting cues: Cast shadows Grouping cues: Similarity (c...

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    Many new digital cameras now detect faces Canon, Sony, Fuji, ... Source: S. Seitz

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    Fingerprint scanners on many new laptops, other devices Face recognition systems now beginning to appear more widely http://www.sensiblevision.com/ Source: S. Seitz

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    Digit recognition, AT&T labs License plate readers http://en.wikipedia.org/wiki/Automatic_number_plate_recognition Source: S. Seitz

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    “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... “ Source:...

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    • A list of companies here: http://www.cs.ubc.ca/spider/lowe/vision.html

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    An introduction to computer vision, its goals, challenges, applications and history. Learn about the perception of images and video, the cues and constraints, and the examples of vision in the real world.

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    • 9MB
    • 74

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  5. link.springer.com › content › pdfIntroduction to Computer Vision - Springer

    Learn about computer vision, its applications, and how it is used in augmented reality on iOS devices. This book covers the basics of computer vision, image processing, and vision tasks with examples and code.

  6. cave.cs.columbia.edu › Statics › monographsIntroduction to Computer Vision - Columbia University

    Feb 5, 2022 · 1. mathematical and physical underpinnings of computer vision. Vision deals with images. We will look at how images are formed and then develop a variety of methods for recovering information about the physical world from images. Along the way, we will show several real-world applications of vision.

  7. cs.brown.edu › courses › cs143CS 143: Introduction to Computer Vision - Brown University

    A PDF file of lecture notes for a course on computer vision at Brown University. It covers topics such as image processing, feature matching, recognition, robotics, and medical imaging.

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  9. vision.stanford.edu › cs131_fall1718 › filesCS 131 Lecture 1: Course introduction - Stanford University

    1 What is computer vision? 1.1 Definition Two definitions of computer vision Computer vision can be defined as a scientific field that extracts information out of digital images. The type of information gained from an image can vary from identification, space measurements for navigation, or augmented reality applications.

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