Flying Object Detection and Classification using Deep Neural Networks
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2019 by IJETT Journal | ||
| Volume-67 Issue-3 |
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| Year of Publication : 2019 | ||
| Authors : Suresh Arunachalam. T, Shahana. R, Vijayasri. R, Kavitha. T |
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| DOI : 10.14445/22315381/IJETT-V67I3P224 |
Citation
MLA Style: Suresh Arunachalam. T, Shahana. R, Vijayasri. R, Kavitha. T "Flying Object Detection and Classification using Deep Neural Networks" International Journal of Engineering Trends and Technology 67.3 (2019): 124-130.
APA Style:Suresh Arunachalam. T, Shahana. R, Vijayasri. R, Kavitha. T (2019). Flying Object Detection and Classification using Deep Neural Networks. International Journal of Engineering Trends and Technology, 67(3), 124-130.
Abstract
Unmanned Aerial Vehicles (UAVs) are extensively used everywhere in commercial applications such as delivering goods and medicines, taking photographs, and to monitor crowded areas. Sometimes these drones are used for capturing our private information without our knowledge. To avoid misuse of UAVs, we need to detect them in advance before entering into the protected areas. Detecting the UAV is a complex task because it is supplemented by birds, aircrafts, moving clouds, and swaying trees. To prevent this, we will detect the drones by video camera. In this paper, we compare the existing computer vision methods such as background subtraction, frame differencing, optical flow and edge detection for object detection. In our work, we will use Convolutional Neural Network for both object detection and classification to enhance its performance.
Reference
[1] Deep Cross-Domain Flying Object Classification for Robust UAV Detection, Arne Schumann, Lars Sommer, Johannes Klatte, Tobias Schuchert, Jurgen Beyerer, IEEE August 2017.
[2] Object Motion Detection Based on Perceptual Edge Tracking, Gao Q, Parslow A,Tan M, IEEE 2016
[3] Unified, Real-Time Object Detection, Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi, IEEE 2016
[4] Using Deep Networks for Drone Detection, Cemal Aker, Sinan Kalkan, IEEE July 2017
[5] FlowNet: Learning Optical Flow with Convolutional Networks, Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Haz?rbas and Vladimir Golkov, IEEE 2015.
[6] Detection and Tracking of Moving Object Based on PTZ Camera, Xinghua Li, Qinglei Chen and Haiyang Chen, IEEE 2012
[7] Moving Object Detection and Locating Based on Region Shrinking Algorithm, Zhihui Li, Haibo Liu and Di Sun, IEEE 2012
[8] A Survey on Different Background Subtraction Method for Moving Object Detection, Rajkumari Bidyalakshmi Devi and Khumanthem Manglem, IEEE 2016
[9] A Study on Detecting Drones Using Deep Convolutional Neural Networks, Muhammad Saqib, abin Sharma, Sultan Daud Khan and Michael Blumenstein, IEEE 2017
[10] A Moving Objects Detection Algorithm in Video Sequence,Mingyang Yang, IEEE 2014
Keywords
Unmanned Aerial Vehicles, Computer Vision, Background Subtraction, Frame Differencing, Optical Flow, Edge detection, Convolutional Neural Networks.