OpenCV: Difference between revisions
m robot Adding: sv:OpenCV |
→External links: -"currently broken 20081001". Link now works - wiki snapshot is available (apparently as of 20081008). |
||
Line 52: | Line 52: | ||
{{Portal|Free software}} |
{{Portal|Free software}} |
||
* [http://opencvlibrary.sourceforge.net/ OpenCV Documentation Wiki] |
* [http://opencvlibrary.sourceforge.net/ OpenCV Documentation Wiki] |
||
* [http://sourceforge.net/projects/opencvlibrary/ OpenCV SourceForge] site |
* [http://sourceforge.net/projects/opencvlibrary/ OpenCV SourceForge] site |
||
* [http://www.cs.iit.edu/~agam/cs512/lect-notes/opencv-intro/opencv-intro.html Introduction to programming with OpenCV] |
* [http://www.cs.iit.edu/~agam/cs512/lect-notes/opencv-intro/opencv-intro.html Introduction to programming with OpenCV] |
Revision as of 16:01, 30 October 2008
Original author(s) | Intel |
---|---|
Repository | |
Operating system | Cross-platform |
Type | Library |
License | BSD license |
Website | http://opencvlibrary.sourceforge.net/ |
OpenCV is a computer vision library originally developed by Intel. It is free for commercial and research use under a BSD license. The library is cross-platform, and runs on Windows, Mac OS X, Linux, VCRT (Real-Time OS on Smart camera) and other embedded operating systems. It focuses mainly on real-time image processing, as such, if it finds Intel's Integrated Performance Primitives on the system, it will use these commercial optimized routines to accelerate itself.
Released under the terms of the BSD license, OpenCV is open source software.
Applications
OpenCV's application areas include
- Human-Computer Interface (HCI)
- Object Identification
- Segmentation and Recognition
- Face Recognition
- Gesture Recognition
- Motion Tracking
- Ego-motion
- Motion Understanding
- Structure from motion (SFM)
- Stereopsis Stereo vision: depth perception from 2 cameras
- Mobile Robotics
To support some of the above areas, OpenCV includes a statistical machine learning library that contains:
- Naive Bayes classifier
- k-nearest neighbor algorithm
- Support Vector Machine
- Decision Trees
- Boosting
- Random forest
- Expectation Maximization
- Neural Networks
Successful applications
- OpenCV was of key use in the vision system of Stanley, the winning entry to the 2005 DARPA Grand Challenge race.
- OpenCV is widely used in video surveillance systems.[1]
- OpenCV is the key tool in the software SwisTrack, an open source multi-agent tracking tool.
- OpenCV has been optimized for the Cell microprocessor. The company that did the port claims a single Playstation 3 running Linux, with only 6 of the 8 SPUs in a full Cell BE, achieves up to 27x the performance of an Intel Core2Duo 2.4 GHz. [2]
Windows prerequisites
The DirectShow SDK is required to build some camera input-related parts of OpenCV on Windows. This SDK is found in the Samples\Multimedia\DirectShow\BaseClasses subdirectory of the Microsoft Platform SDK, which must be built prior to the building of OpenCV.
References
- Learning OpenCV: Computer Vision with the OpenCV Library Book by O'Reilly press.