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Static And Dynamic Object Tracking And Detection


POWER-NORMALIZED CEPSTRAL COEF

CCTV object detection with fuz

Vision Guided Pick and Place R
Abstract


Nowadays CCTVs are installed at many places like banks safe. But the CCTV cameras continuously record the situations. Hence there is unnecessary memory wastage if there is nothing happening in front of the camera. Also the CCTV system does not provide alerts of burglary happening at particular time. So there is a need of a system which will record the situation only if there is some movement happening in front of the camera and send alerts to the manager as well as the police. By implementing the system in real time and testing the system on large number of long sequences, authenticated person can stop alert for fix time to enter into secured area by remote login. Human motion Detection System is developed from the security point of view. The objective of Real Time Security System using Human Motion Detection is to develop a system that monitors the area in which it is being deployed. In Human motion detection System, web camera is applicable in the area where no one is permissible to enter, also where we need to detect if any motion has been done. We can use camera for Human Motion Detection .The Camera is used to catch the live images of the area in which it is being implemented, if any object is moving. Within the collaborative appearance model, using a sparse discriminative classier (SDC) and sparse generative model (SGM) for object tracking. In the SDC module, for separating the foreground object from the background based on holistic we present a classier. In the SGM module, a histogram-based method that takes the spatial information of each local patch into consideration. If motion is found in this video, the computer will start recording, send SMS with URL to people listed in its database. In this way the system will provide the security against any misdeed.

KeyWords
Feature Extraction, Motion detection, Sparse Discriminative Classifier, Sparse Generative Model.



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