Natural-Inspired Drone Swarm Processing Fov For Efficient Multi-View Monitoring And Object Detection

Osama ElSayed , Sherine Youssef , Ossama Ismail

Unmanned Aerial Vehicles, Drones, Multi-UAV, Object detection, Video stitching, video stabilization

The rising interest in aerial swarm drones, a type of multi-agent robotic system, has sparked potential applications. This paper presents the Intelligent Model Using Swarm Drones for Surveillance Applications. It proposes the use of commercially available DJI Tello drones for unmanned aerial vehicle (UAV) swarm missions as a cost-effective alternative to custom-made drones. To enable simultaneous control of multiple drones and introduce real-time video stitching, a camera path estimation and homography refinement method will be used. The paper aims to contribute to the surveillance swarm drone industry by decreasing data transfer, storage, management, and monitoring, using efficient multi-view panoramic imaging and extra compression of surveillance swarm drones' cameras' footage through stitching. To enhance video stitching stability, a unified framework for joint video stitching and stabilization is proposed. This approach involves creating an optimal virtual 2D camera path from the original paths, space-temporal optimization that considers inter and intra motions, grid-based tracking for improved robustness, and mesh-based motion models to handle scene parallax in videos captured simultaneously by multiple moving cameras that may exhibit shaking and artifacts when directly applying image stitching methods.

Published Paper   E-Certificate

" Natural-Inspired Drone Swarm Processing Fov For Efficient Multi-View Monitoring And Object Detection", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.e157-e173, March-2023, Available :https://ijnrd.org/papers/IJNRD2303421.pdf

Volume 8 Issue 3, March-2023

Pages : e157-e173

Paper Reg. ID: IJNRD_189553

Published Paper Id: IJNRD2303421

Downloads: 000118918

Research Area: Computer Engineering 

Country: Alexandria, Alexandria, Egypt

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303421

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303421

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition