Computer Vision with the OpenCV LibraryGary Bradski and Adrian Kaehler

Natalia Taborda Restrepo

Universidad Nacional de Colombia, Sede Medellin

Noviembre, 2011

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What Is OpenCV?

OpenCV is an open source (see http://opensource.org)computer visionlibrary available from http://SourceForge.net/projects/opencvlibrary.OpenCV is writdten in optimized C and and can take advantage of multicoreprocessors and runs under Linux, Windows and Mac OS X. OpenCV wasdesigned for computational efficiency and with a strong focus on realtimeapplications.

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What Is OpenCV?

One of OpenCV’s goals is to provide a simple-to-use computer vision infrastructure that helps people build fairly sophisticated

vision applications quickly. The OpenCV library contains over 500 functions that span many areas in vision, including factory

product inspection, medical imaging, security, user interface, camera calibration, stereo vision, and robotics.

¡No more reinventing the wheel!

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What Is OpenCV?

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Computer Vision

Figure: To a computer, the car’s side mirror is just a grid of numbers

In this picture we see a side mirror on the driver’s side of the car. What the

computer ”sees” is just a grid of numbers. Any given number within that grid has

a rather large noise component and so by itself gives us little information, our

task then becomes to turn this noisy grid of numbers into the perception: ”side

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Figure: The ill-posed nature of vision:the 2D appearance of objects can change radically with viewpoint

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Speeding Up OpenCV with IPP

If you desire further automatic optimization on Intel architectures [Intel],you can buy Intel’s Integrated Performance Primitives (IPP) libraries [IPP],which consist of low-level optimized routines in many different algorithmicareas. OpenCV automatically uses the appropriate IPP library at runtime if

that library is installed.

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OpenCV Structure and Content

OpenCV is broadly structured into five main components, four of which are shown

in the next Figure.

Figure: The basic structure of OpenCV

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CvAux

CvAux is not particularly well documented in the Wiki and is not docu-mented at all in the .../opencv/docs subdirectory. CvAux covers:

Eigen objects, a computationally efficient recognition technique thatis, in essence, a template matching procedure.

1D and 2D hidden Markov models, a statistical recognition techniquesolved by dynamic programming.

Embedded HMMs (the observations of a parent HMM are themselvesHMMs).

Gesture recognition from stereo vision support.

Extensions to Delaunay triangulation, sequences, and so forth.

Stereo vision.

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CvAux

Shape matching with region contours.

Texture descriptors.

Eye and mouth tracking.

3D tracking.

Finding skeletons (central lines) of objects in a scene.

Warping intermediate views between two camera views.

Background-foreground segmentation.

Video surveillance (see Wiki FAQ for more documentation).

Camera calibration C++ classes (the C functions and engine are inCV).

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Portability

Figure: OpenCV portability guide for release 1.0: operating systems are shown on the left; com- puter architecture types

across top

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