Visible to the public Human Detection and Tracking on Surveillance Video Footage Using Convolutional Neural Networks

TitleHuman Detection and Tracking on Surveillance Video Footage Using Convolutional Neural Networks
Publication TypeConference Paper
Year of Publication2019
AuthorsDinama, Dima Maharika, A’yun, Qurrota, Syahroni, Achmad Dahlan, Adji Sulistijono, Indra, Risnumawan, Anhar
Conference Name2019 International Electronics Symposium (IES)
Date Publishedsep
ISBN Number978-1-7281-4449-8
Keywordsconvolutional neural nets, convolutional neural networks, Deep Learning, Deep Learning Convolutional Neural Networks, deep video, human behaviour, human detection, human detection framework, human position, human tracking, image filtering, image recognition, learning (artificial intelligence), Metrics, object detection, pubcrawl, resilience, Resiliency, Scalability, security system, spatial correlation filter, Surveillance video, surveillance video footage, tracked movement, tracking algorithm, tracking algorithms, video signal processing, video surveillance

Safety is one of basic human needs so we need a security system that able to prevent crime happens. Commonly, we use surveillance video to watch environment and human behaviour in a location. However, the surveillance video can only used to record images or videos with no additional information. Therefore we need more advanced camera to get another additional information such as human position and movement. This research were able to extract those information from surveillance video footage by using human detection and tracking algorithm. The human detection framework is based on Deep Learning Convolutional Neural Networks which is a very popular branch of artificial intelligence. For tracking algorithms, channel and spatial correlation filter is used to track detected human. This system will generate and export tracked movement on footage as an additional information. This tracked movement can be analysed furthermore for another research on surveillance video problems.

Citation Keydinama_human_2019