Penghitung orang pada video CCTV menggunakan metode histogram of oriented gradient dan filter Kalman

People counter on CCTV video using histogram of oriented gradient and Kalman filter methods

Faisal Dharma Adhinata  -  Master of Computer Science, Universitas Gadjah Mada, Indonesia
Muhammad Ikhsan  -  Master of Computer Science, Universitas Gadjah Mada, Indonesia
*Wahyono Wahyono orcid scopus  -  Department of Computer Science and Electronic, Universitas Gadjah Mada, Indonesia
Received: 7 Feb 2020; Revised: 12 May 2020; Accepted: 26 May 2020; Published: 31 Jul 2020; Available online: 8 Jun 2020.
Open Access Copyright (c) 2020 Jurnal Teknologi dan Sistem Komputer
License URL: http://creativecommons.org/licenses/by-sa/4.0

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Article Info
Section: Original Research Articles
Language: ID
Statistics: 355 62
Abstract
CCTV cameras have an important function in the field of public service, especially for convenience. The objects recorded through CCTV cameras are processed into information to support service satisfaction in the community. This study uses the function of CCTV for people counting from objects recorded by a camera. Currently, the process of detecting and tracking people takes a long time to detect all frames. In this study, the frame selection into keyframes uses the mutual information entropy method. The keyframes processing uses the Histogram of Oriented Gradient (HOG) and Kalman filter methods. The proposed method results F1 value of 0.85, recall of 76 %, and precision of 97 % with winStride parameter (12,12), scale 1.05, and the distance of the human object to CCTV 4 meters.
Keywords: HOG; Kalman filter; mutual information entropy; people counting; people detection

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