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Image Processing and ComputerVision
Ranga RodrigoDepartment of Electronic and Telecommunication Engineering
University of MoratuwaSri Lanka
Mathematics Society Talk
February 24, 2009
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Outline
1 Introduction
2 Applications
3 Vision in Automation
4 Software Tools
5 Examples of State-of-the-Art
6 Summary
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Introduction
What Is Image Processing?
Image ProcessingIn image processing, we attempt to manipulate theinput image to obtain a “better” image.
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Introduction
What Is Computer Vision?
Computer VisionIn computer vision, we analyze the input image andobtain an understanding or make a decision.
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Introduction
What Is Computer Vision?
The goal is the emulation of the visual capabilityof human beings using computers.In other words, computer vision is making themachine see as we do!It is challenging.Steps:
1 Image acquisition2 Image manipulation3 Image understanding4 Decision making
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Introduction
Main Driving Technologies
Signal processing.Multiple view geometry [2].Optimization.Machine learning.Hardware and algorithms.
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Applications
Applications 1
Automotive:Lane departure warning systems.Head tracking systems for drowsiness detection.Driver assistance systems.Reading automobile license plates, and trafficmanagement.
Photography:In camera face detection [5], red eye removal, andother functions.Automatic panorama stitching [1].
1(From http://www.cs.ubc.ca/spider/lowe/vision.html)Mathematics Society Talk Image Processing and Computer Vision 9/35
Applications
ApplicationsMovie and video (a very big industry):
Augmented reality.Tracking objects in video or film and solving for 3-Dmotion to allow for precise augmentation with 3-Dcomputer graphics.Multiple cameras to precisely track tennis and cricketballs.Human expression recognition.Software for 3-D visualization for sportsbroadcasting and analysis.Tracking consistent regions in video and insertvirtual advertising.Tracking for character animation.Motion capture, camera tracking, panoramastitching, and building 3D models for movies.
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Applications
Camera Tracking
Source: http://www.2d3.com/capability
Show 2d3 video.
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Applications
ApplicationsGames:
Tracking human gestures for playing games orinteracting with computers.Tracking the hand and body motions of players (tocontrol the Sony Playstation).Image-based rendering, vision for graphics.
General purpose:Inspection and localization tasks, people counting,biomedical, and security. etc.Object recognition and navigation for mobilerobotics, grocery retail, and recognition from cellphone cameras.Laser-based 3D vision systems for use on the spaceshuttles and other applications.Image retrieval based on content.
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Applications
ApplicationsIndustrial automation (a very big industry):
Vision-guided robotics in the automotive industry.Electronics inspection systems for componentassembly.
Medical and biomedical (maturing):Vision to detect and track the pose of markers forsurgical applications, needle insertion, and seedplanting.Teleoperations.Quantitative analysis of medical imaging, includingdiagnosis such as cancer.
Security and biometrics (thriving):Intelligent video surveillance.Biometric face, fingerprint, and iris recognition.Behavior detection.
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Applications
Minimal Invasive Surgery
Source: http://www.davincisurgery.com/surgery/system/index.aspx
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Applications
Areas of Advancement
Hardware.Image segmentation.3-D reconstruction.Object detection.Navigation.Scene understanding.
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Vision in Automation
What’sneeded?
cameras
software
actuators
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Vision in Automation
Cameras
Camera, and a frame grabber.IEEE 1394 or USB cameras.Ethernet cameras.
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Vision in Automation
Source: http://www.ptgrey.com/products/chameleon/index.asp
Source: http://www.matrox.com/imaging/products/vio/home.cfm
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Vision in Automation
Source: http://www3.elphel.com/sites/default/files/images/nc353 io geo.jpeg
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Software Tools
Software Tools
Octave or Matlab.C or C++ with a library such as OpenCV.
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Software Tools
Image Processing using Octave orMatlab
Simple and quick.A lot of library functions.Interpreted.
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Software Tools
Octave Examples
Image reading and writing.Histograms.Filtering.
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Software Tools
Image Processing using OpenCV
Power of C++.Well coded.
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Software Tools
OpenCV Examples
1 Image reading and writing.2 Edge detection.3 Template matching.4 Capturing video.
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Examples of State-of-the-Art
Segmentation Using Graph Cuts [4]
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Examples of State-of-the-Art
3-D Reconstruction
Can we obtain a 3-D view of a scene, given onlya set of (2-D) images?Yes. Using multiple view geometry, we canreconstruct a scene.Show Leibe et al. video [3].
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Examples of State-of-the-Art
Object Detection: Face Detection
Show OpenCV sample.Mathematics Society Talk Image Processing and Computer Vision 30/35
Examples of State-of-the-Art
Navigation: Sanford’s Robot Stanley
Show video.
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Summary
Conclusion
Vision-based automation is promising.Solutions are simple in a controlledenvironment.State-of-the-art is very interesting.
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Summary
Thank you.
OpenCV examples, and Octave examples are here:http://www.ent.mrt.ac.lk/ ranga/publications.html
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Summary
Matthew Brown and David Lowe.Recognising panoramas.In Proceedings of the 9th International Conference on Computer Vision, pages1218–1225, Nice, France, October 2003.
Richard Hartley and Andrew Zisserman.Multiple View Geometry in Computer Vision.Cambridge University Press, 2nd edition, 2003.
Bastian Leibe, Nico Cornelis, Kurt Cornelis, and Luc Van Gool.Dynamic 3D scene analysis from a moving vehicle.In Proceedings of the IEEE Computer Society Conference on Computer Vision andPattern Recognition, pages 1–8, Minneapolis, MN, June 2007.
Carsten Rother, Vladimir Kolmogorov, and Andrew Blake.“GrabCut”: Interactive foreground extraction using iterated graph cuts.ACM Transactions on Graphics: Proceedings of the 2004 SIGGRAPH Conference,23(3):309–314, August 2004.
Paul Viola and Michael Jones.Rapid object selection using a boosted cascade of simple features.In Proceedings of the IEEE Computer Society Conference on Computer Vision andPattern Recognition, pages 511–518, Hawaii, December 2001.
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