PROJECT TITLE :
Fast Recognition Of Human Climbing Fences In Transformer Substations - 2017
Recognition of human climbing fences in trans-former substations is very essential in an exceedingly power substation. This paper proposed an innovative and practical human climbing fences detection method primarily based on image processing. At 1st, the Gaussian Mixture Model background modelling algorithm is exploited to detect motion objects beneath a read of fix surveillant camera in a very power substation. After getting the motion regions of interest, the Histogram of Oriented Gradient (HOG) feature is extracted to describe inner human. And then, based on the results of HOG feature extraction, the Support Vector Machine (SVM) is trained to classify pedestrians. Next, an improved Hough Rework is implemented to detect fences. Finally a Sparse Optical Flow methodology is applied to trace the motion of human. Compelling experimental results demonstrated the correctness and effectiveness of our proposed methodology.
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