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Changjae Oh
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Computer Vision
– Introduction –
Semester 1, 22/23
What is coming?
What is missing?
Machines are blind Machine vs Human
Computer Vision in Four Words?
Making computers understand images
How simple is that?
Mentimeter
Computer Vision in Four Words?
:: Making computers understand images
• How many people are here?
• Who is a person in the portrait?
• What is this building?
• How is the weather?
• Where is this city?
• What is written?
• Is there any gate?
Computer Vision in Four Words?
:: Making computers understand images
• How many people are here?
• Who is a person in the portrait?
• What is this building?
• How is the weather?
• Where is this city?
• What is written?
• Is there any gate?
→ Object detection
→ Face detection/recognition
→ Object recognition
→ Scene recognition
→ Place recognition
→ Character recognition
→ Object detection
What is vision?
• What does it mean, to see? “to know what is where by looking”.
• How to discover from images what is present in the world, where things are, what actio
ns are taking place.
• “Vision can be understood as an information processing task which converts a numerical
image representation into a symbolic shape-oriented representation.”
Credit: Marr, 1982
Why is vision so hard?
• 3D: Viewpoint
Why is vision so hard?
• 3D: Viewpoint
Why is vision so hard?
Credit: A. Torralba
Why is vision so hard?
Credit: A. Torralba
Why is vision so hard?
Why is vision so hard?
• Transparent objects
Credit: Hengyi Wang (JP Final project 2021)
http://corsmal.eecs.qmul.ac.uk/
http://corsmal.eecs.qmul.ac.uk/
Why is vision so hard?
• What is this object?
Why is vision so hard?
• What is this object?
Why is vision so hard?
• What is this object?
It is not just about pixels!
Computer Vision and Image Processing?
• Computer Vision begins with Image Processing!
• Computer Vision: techniques for enabling a computer to see a real-world using images
as the human being does.
• Image Processing: fundamental techniques for image acquisition, processing, analysis
Mathematics
Signal Processing
Image ProcessingAudio Processing
Machine Learning
Artificial Intelligence
Computer Vision…..
Computer Vision and EBUxxxx?
Multimedia
Fundamentals
Transform Methods
VisionEBU6230
Video Processing
EBU7240: Low-level Vision
High-level vision
• Classification
• Detection
• Tracking
• Action & Pose
Low-level vision
• Enhancement
• Restoration
• Filtering
• Feature extraction
Mid-level vision
• Grouping
• 3D geometry
• 3D reconstruction
• Tracking
EBU7240: Mid-level Vision
High-level vision
• Classification
• Detection
• Tracking
• Action & Pose
Low-level vision
• Enhancement
• Restoration
• Filtering
• Feature extraction
Mid-level vision
• Grouping
• 3D geometry
• 3D reconstruction
• Tracking
EBU7240: High-level Vision
High-level vision
• Classification
• Detection
• Tracking
• Action & Pose
Low-level vision
• Enhancement
• Restoration
• Filtering
• Feature extraction
Mid-level vision
• Grouping
• 3D geometry
• 3D reconstruction
• Tracking
EBU7240: Deep learning approach
• Multiple levels of (learned) representation
Changjae Oh
Computer Vision
– Applications –
Semester 1, 22/23
Why computer vision matters?
Safety Health Security
Comfort Fun Access
Ridiculously brief history of computer vision
• 1966: Minsky assigns computer vision as an undergrad
summer project
• 1960’s: interpretation of synthetic worlds
• 1970’s: some progress on interpreting selected images
• 1980’s: ANNs come and go; shift toward geometry and
increased mathematical rigor
• 1990’s: face recognition; statistical analysis in vogue
• 2000’s: broader recognition; large annotated datasets
available; video processing starts
• 2010’s: Deep learning with ConvNets
• 2020’s: Widespread autonomous vehicles?
• 2030’s: robot uprising?
Slide credit: J. ‘68
Turk and Pentland ‘91
Applications – Motion capture
Microsoft XBox Kinect
Applications – Face recognition
https://www.cl.cam.ac.uk/~jgd1000/afghan.html
Applications – Face Alignment
http://jbhuang0604.blogspot.com/2013/04/miss-korea-2013-contestants-face.html
https://www.maccosmetics.co.uk/virtual-try-on
Applications – Smile detection
Slide credit:
Applications – Optical character recognition (OCR)
Slide credit:
Applications – Defect detection
https://deepsystems.ai/solutions/road-defects-detection
Applications – Cleaning robot
https://www.popsci.com/new-roomba-knows-location/
Applications – Sports
Intel Replay Technology Delivers All-Star Experience for MLB Fans
Applications – Object recognition
Applications – 3D from mobile phone
Applications – Indoor scene reconstruction
Applications – Video Matting/Composition
Applications – Style Transfer
A Neural Algorithm of Artistic Style [Gatys et al. 2015]
Applications – Self-driving cars
Applications – Healthcare
Why is computer vision timely?
• Lots of image data is being collected
Why is computer vision timely?
• Lots of image data is being collected
̶ Bigger data is coming
Why is computer vision timely?
• There is a lot of information in images
Why is computer vision timely?
• Computer vision is starting to work …
http://www.sony-asia.com/article/271940/section/product/product/dsc-wx1
50 years ago
Slide credit: A. Torralba
10 years ago…
Slide credit: A. Torralba
Next topic
• Let’s talk about a computer’s eye (a.k.a. camera)
̶ Prerequisite
• Review EBU6230 Image/Video Processing – Week2: Image Transformations
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