Target tracking using webcams
With rapid proliferation of video cameras in public places and ever decreasing price/performance ratio of computing, the ability to identify and track people creates tremendous opportunities for important business and security applications. This report presents a sub-project of the Multiple Camera I...
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sg-ntu-dr.10356-207652023-07-07T16:00:37Z Target tracking using webcams Nyan Win. Xie Lihua School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation With rapid proliferation of video cameras in public places and ever decreasing price/performance ratio of computing, the ability to identify and track people creates tremendous opportunities for important business and security applications. This report presents a sub-project of the Multiple Camera Indoor Surveillance system. In this project, two webcams are connected to a computer in which C language platform with OpenCV libraries (open source) are installed and knowledge based techniques are used to track and localize a person in a predetermined area. Using built-in Haar-like feature detection classifiers in OpenCV, we can identify human faces and subtract them out of the background which is normally unchanged and is really not of interest. Haar-like features encode some information about the class (face in this project) to be detected using the existence of oriented contrasts between regions in the image. Bachelor of Engineering 2010-01-07T07:57:53Z 2010-01-07T07:57:53Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/20765 en Nanyang Technological University 53 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation Nyan Win. Target tracking using webcams |
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With rapid proliferation of video cameras in public places and ever decreasing price/performance ratio of computing, the ability to identify and track people creates tremendous opportunities for important business and security applications. This report presents a sub-project of the Multiple Camera Indoor Surveillance system. In this project, two webcams are connected to a computer in which C language platform with OpenCV libraries (open source) are installed and knowledge based techniques are used to track and localize a person in a predetermined area.
Using built-in Haar-like feature detection classifiers in OpenCV, we can identify human faces and subtract them out of the background which is normally unchanged and is really not of interest. Haar-like features encode some information about the class (face in this project) to be detected using the existence of oriented contrasts between regions in the image. |
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Xie Lihua |
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Xie Lihua Nyan Win. |
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Final Year Project |
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Nyan Win. |
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Nyan Win. |
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Target tracking using webcams |
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Target tracking using webcams |
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Target tracking using webcams |
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Target tracking using webcams |
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Target tracking using webcams |
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target tracking using webcams |
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2010 |
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http://hdl.handle.net/10356/20765 |
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