OPEN CV – AN INTRODUCTION TO THE VISION LIBRARY AND ITS APPLICATIONSHemanth HaridasCo founder VidPulp Technologies
WHAT IS THIS TALK ABOUT? An basic introduction to Open CV, a cross
platform vision library. To get students interested in Vision and
related fields. Introduction to the capabilities of Open CV. Applications of the library. Limitations of the library
WHAT IS THIS TALK NOT ABOUT? Not a programmatic tutorial on Open CV. Not a detailed explaination about Open CV. No math behind Open CV covered.
COMPUTER VISION Rapidly growing field because of cheaper and
more capable cameras and affordable processing power.
Vision algorithms are starting to mature. Open CV has helped computer vision grow as
a field Open CV helps jump-start research by
providing them with a computer vision and machine learning infrastructure
CONTENTS Introduction Who Uses OpenCV? What is Computer Vision? How complex is the problem? Details about the Library. Summary
INTRODUCTION OpenCV (Open Source Computer Vision) library of programming functions for real
time computer vision. (computer efficiency) Written in optimized C and C++ Runs in windows, Linux and MAC OS. Can develop in C, C++, python, ruby, matlab
INTRODUCTION Simple to use infra Helps to build fairly complicated applications. 500 functions spanning
Factory product inspection medical imaging Security user interface camera calibration stereo vision robotics
contains a full, general-purpose Machine Learning Library (MLL)
WHO USES OPEN CV? Surveillance images and video on the Web. (Flickr, picasa
face recognition and tagging) aerial and street-map images (such as in
Google’s Street View) make heavy use of camera calibration and image stitching techniques
safety monitoring, unmanned flying vehicles, or biomedical analysis.
manufacturing: virtually everything that is mass-produced has been automatically inspected at some point using computer vision.
WHO USES OPEN CV? license for OpenCV has been structured such
that you can build a commercial product using all or part of OpenCV.
You are under no obligation to opensource large user community that includes people
from major companies (IBM, Microsoft , Intel, SONY, Siemens, and Google, to name only a few) and research centers (such as Stanford, MIT, CMU, Cambridge, and INRIA).
WHO USES OPEN CV? http://groups.yahoo.com/group/OpenCV - 20,000
members OpenCV was a key part of the vision system in the
robot from Stanford, “Stanley”, which won the $2M DARPA Grand Challenge desert robot race
web maps, image scan alignment, medical image noise reduction, object
analysis, security and intrusion detection systems, automatic monitoring and safety systems,
manufacturing inspection systems, camera calibration, military applications, and
unmanned aerial, ground, and underwater vehicles
WHAT IS COMPUTER VISION? transformation of data from a still or video
camera into either a decision or a new representation.
Data - > “the camera is mounted in a car” or “laser range fi nder indicates an object is 1 meter away”.
Decision -> “there is a person in this scene” or “there are 14 tumor cells on this slide”
new representation -> turning a color image into a grayscale image
HOW HARD CAN THAT BE? Human brain divides the vision signals to
many channels. Identifies important parts Complex feedback mechanism that is little
understood. draw on cross-associations made from years
of living in the world. Controls lighting through the iris.
HOW A MACHINE SEES IT? A 2d Image of a 3d object. No definite way to reconstruct the 3d image.
HOW A MACHINE SEES IT? Images are corrupted by noise and distortions. (weather, lighting, reflections, movements)
• Additional contextual knowledge is used
• Which is helpful in matching
NOISE Edge Detection -> impossible to detect
edges by comparing a point to its neighbours If the comparison is made over a localized
area its easier. Compensating noise by using statistics over
time. Explicit models learnt from available data.
(lens distortions)
CONTEXTUAL INFORMATION The decision taken by vision algorithms
depend on the application it is used for. Security system that alerts if a person tries
to cross a fence. monitoring system that counts how many
people cross through an area in an amusement park.
Strategy for vision algos in security cameras different from that of in robots.
The more constrained our context , the better the solution will be.
ABOUT THE LIBRARY aimed at providing the basic tools needed to
solve computer vision problems high-level functionalities in the library will be
sufficient to solve the more complex problems in computer vision
the basic components in the library are complete enough to enable creation of a complete solution
After you develop a first draft solution, check for weakness and fix it.
OPEN CV TIMELINE
COMPONENTS OF OPENCV
RESOURCES Download Open CV -
http://sourceforge.net/projects/opencvlibrary/ Install guide and tutorials -
http://opencv.willowgarage.com/wiki/ IDE – eclipse, .net , VC++
SUMMARY Open CV is a open source library to
implement Computer vision algorithms Computer vision is a complex problem. Made easy with enough context information. Computer vision is a interesting and a fast
growing field and skills in this field is niche , in demand
OCR ALGORITHMS Optical character recognition, to recognize
text in scanned documents. Useful in detecting text in videos For extracting contextual information in
videos. Tesseract and GOCR – open source OCRs
available
SPEECH TO TEXT ALGOS Algorithms to convert from Speech to text. Text to speech conversion algos are
available. Language translation research is underway.
QUESTIONS?
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