This work proposes a method for detecting and tracking moving objects that rely onthe partial differential equation technique and can track both forward and backward. In orderto reduce the amount of noise in the output video, it is first divided into many frames andthen pre-processed using methods for the Gaussian filters. The transfer function is calculatedon the binarized frames following the acquisition of the absolute difference for forwardtracking and backward tracking. The forward and backward tracking outputs are combined atthe object tracking step to get the desired outcome. Statistics like f-measure, accuracy,retention, and precision are used to evaluate the predicted technique, and classic motiondetection methods are also used to examine its effectiveness. According to the evaluationresults, the suggested system is superior to the usual high-accuracy rate techniques.
Keywords
Object Tracking, Partial Derivative, Video Framing, Object Motion, Transfer Function.
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Hannah Rose Esther T
Hannah Rose Esther T
Department of Computer Science and Engineering, AMET University, Chennai, India.
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Cite this article
Hannah Rose Esther T and Duraimutharasan N, “An Automated Partial Derivative-Based Method for Detecting and Monitoring Moving Objects”, Journal of Machine and Computing, vol.3, no.4, pp. 486-496, October 2023. doi: 10.53759/7669/jmc202303040.
