Human Detection in Video Surveillance

Sushama Khanvilkar; Santosh Gupta; Hinal Rane; Calvin Galbaw

doi:10.24071/ijasst.v3i1.2747

Human Detection in Video Surveillance

Sushama Khanvilkar⁽¹⁾, Santosh Gupta⁽²⁾, Hinal Rane⁽³⁾, Calvin Galbaw^(4*),

(1) Xavier Institute of Engineering, Mumbai, India
(2) Xavier Institute of Engineering, Mumbai, India
(3) Xavier Institute of Engineering, Mumbai, India
(4) Xavier Institute of Engineering, Mumbai, India
(*) Corresponding Author

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.

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References

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DOI: https://doi.org/10.24071/ijasst.v3i1.2747