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All Journal International Journal of Applied Sciences and Smart Technologies
Sushama Khanvilkar
Xavier Institute of Engineering, Mumbai, India
Computer Science & IT Energy Engineering Industrial & Manufacturing Engineering

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Human Detection in Video Surveillance Sushama Khanvilkar; Santosh Gupta; Hinal Rane; Calvin Galbaw
International Journal of Applied Sciences and Smart Technologies Volume 03, Issue 01, June 2021
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v3i1.2747

Abstract

Recognition of the human activities in videos has gathered numerous demands in various applications of computer vision like Ambient Assisted Living, intelligent surveillance, Human-Computer interaction.One of the most pioneering techniques for Human Detection in Video Surveillance based on deep learning and this project mainly focuses on various approaches based on that. This paper provides an idea of solution to use video surveillance more effectively, by detecting any humans present and notifying the concerned people. The deep learning model, preferred for fast computation, Convolution Neural Network is used by stacking 3 blocks of layers on fully connected layers. This provided an identification of humans and naïve approach to eliminate inanimate humanlike objects such as mannequins.
Co-Authors Calvin Galbaw Hinal Rane Santosh Gupta