Paper Title

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

Article Identifiers

Registration ID: IJNRD_189553

Published ID: IJNRD2303421

DOI: Click Here to Get

Authors

Osama ElSayed , Sherine Youssef , Ossama Ismail

Keywords

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

Abstract

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.

How To Cite (APA)

Osama ElSayed, Sherine Youssef, & Ossama Ismail (March-2023). Natural-Inspired Drone Swarm Processing Fov For Efficient Multi-View Monitoring And Object Detection. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(3), e157-e173. https://ijnrd.org/papers/IJNRD2303421.pdf

Issue

Volume 8 Issue 3, March-2023

Pages : e157-e173

Other Publication Details

Paper Reg. ID: IJNRD_189553

Published Paper Id: IJNRD2303421

Downloads: 000121986

Research Area: Computer Engineering 

Country: Alexandria, Alexandria, Egypt

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

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

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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

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Call For Paper

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

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