Computer Vision

CS302 Data Structures

Dr. George Bebis

http://www.cse.unr.edu/CVL

What is Computer Vision?

Nice sunset!

“Making computers see and understand”

Connections to other disciplines

Computer Vision

Image Processing

Pattern Recognition

Machine Learning

Artificial Intelligence

Robotics

PsychologyNeuroscience

Computer Graphics

Image Processing

Image Processing (cont’d)

• Image enhancement

• Image Compression

Computer Graphics

Computer Graphics (cont’d)

Image

Output:

Geometric ModelsSyntheticCamera

projection, shading, lighting models

Computer Vision

Computer Vision (cont’d)

Model

Output:

Real Scene

Cameras Images

Why is Computer Vision Difficult?

(1) It is a many-to-one mapping.– Inverse mapping has non-unique

solution.

– A lot of information is lost in the transformation from the 3D world to the 2D image.

(2) It is computationally intensive.- A typical video is 30 frames / sec

(3) We do not understand the recognition problem.

Viewpoint variations

Michelangelo 1475-1564

Illumination changes

Scale changes

Deformations

Occlusions

Background clutter

Motion blurring

Intra-class variation

Local ambiguity

Applications

• Industry (visual inspection and assembly)

• Security and Surveillance (object detection, recognition, and tracking)

• Human Activity Recognition

• Traffic Monitoring and Analysis

• Robotics

• Medical Applications

• Many more …

Industrial Computer Vision (Machine Vision)

Industrial computer vision systems work really well.

Make strong assumptions about lighting conditions

Make strong assumptions about the position of objects

Make strong assumptions about the type of objects

Visual Inspection

COGNEX

Optical character recognition (OCR)

Digit recognition, AT&T labshttp://yann.lecun.com/exdb/lenet/

• Technology to convert scanned docs to text

License plate readershttp://en.wikipedia.org/wiki/Automatic_number_plate_recognition

Automatic check processing

Biometrics

Login without a password…

Fingerprint scanners on many new laptops,

other devices

Face recognition systems begin to appear more widely

http://www.sensiblevision.com/

Face Recognition: Apple iPhoto

http://www.apple.com/ilife/iphoto/

Face detection

• Many new digital cameras now detect faces– Canon, Sony, Fuji, …

Smile detection?

Sony Cyber-shot® T70 Digital Still Camera

How the Afghan Girl was Identified by Her Iris Patterns

Iris Biometrics

Hand-based Biometrics

Object Recognition (in supermarkets)

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… “

Mobile visual search: Google Goggles

http://www.google.com/mobile/goggles/

Visual Surveillance and Human Activity Recognition

Surveillance and security

Traffic Monitoring

http://www.honeywellvideo.com/

Smart cars:

– Vision systems currently in high-end BMW, GM, Volvo models.

Mobileye

Automatic Panorama Stitching

Automatic Panorama Stitching (cont’d)

find correspondences

3D Modeling

Medical Imaging

Skin/Breast Cancer Detection

3D imagingMRI, CT

Enable surgeons to visualize internal structures through an automated overlay of 3D reconstructions of internal anatomy on top of live video views of a patient.

Image guided surgeryGrimson et al., MIT

Robotics

http://www.robocup.org/

Semantic Robot Vision Challengehttp://www.semantic-robot-vision-challenge.org/http://www.youtube.com/watch?v=GItjILILB50

Vision in space

• 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 Exploration Rover Spirit captured this westward view from atop a low plateau where Spirit spent the closing months of 2007.

Vision-based Interaction and Games

Nintendo Wii has camera-based IRtracking built in. See Lee’s work atCMU on clever tricks on using it tocreate a multi-touch display!

Assistive technologies

Kinect

Movie Special Effects

Movie special effects• Insert synthetic objects in real image sequences;.

• Change artificially the position or the orientation of a camera.

• Freeze a moving 3D scene.

Computer Vision Jobs !!

• Academia– MIT, UC-Berkeley, CMU, UIUC, USC …… UNR!

• National Labs and Government– Los Alamos National Lab– Lawrence Livermore National Lab– Navy, Air-force, Army

• Industry– Microsoft, Intel, IBM, Xerox, Compaq, Siemens, HP, TI, Motorola, Phillips, Honeywell, Ford

http://www.cs.ubc.ca/spider/lowe/vision.html

See:

What skills would you need to succeed in this field?

• Strong programming skills (i.e., C, C++, Matlab)

• Very good knowledge of Data Structures and Algorithms

• Very good background in Mathematics, especially in:– Calculus

– Linear Algebra

– Probabilities and Statistics

– Numerical Analysis

– Geometry

Related Courses at UNR

• CS474/674 Image Processing and Interpretation (every Fall)• CS485/685 Computer Vision (every Spring)• CS486/686 Advanced Computer Vision (every Fall)• CS479/679 Pattern Recognition (every other Spring)• Special Topics

– Biometrics, Object Recognition, Neural Networks,– Mathematical Methods for Computer Vision

• CS482/682 Artificial Intelligence• CS773A Machine Intelligence• CS791Q Machine Learning• CS480/680 Computer Graphics

CS474/674 Image Processing

• 2 exams

• Homework

• 5-6 programming assignments

noise elimination light correctioncontrast enhancement

CS485/685 Computer Vision

• Two exams

• Homework

• 5-6 programming assignments

• Paper presentations (grad students)

face recognition 3D reconstructionobject recognition

More information on Computer Vision

• Computer Vision Home Page http://www.cs.cmu.edu/afs/cs/project/cil/ftp/html/vision.html

• UNR Computer Vision Laboratory http://www.cs.unr.edu/CVL