Object Tracking Framework for Unmanned Aerial Vehicles

Ahmed Dirir; Hesham Elsayed

doi:10.1109/GCIoT47977.2019.9058406

Object Tracking Framework for Unmanned Aerial Vehicles

Ahmed Dirir, Hesham Elsayed

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

Object tracking is a computer vision problem that gained attention in the past few decades. Numerous algorithms targeting various challenges associated with object tracking have been proposed to address issues related to multiple objects tracking, handling complex scenarios like fog and occlusions, and other subproblems within the object tracking area. On the other hand, the extensive use of Unmanned Aerial Vehicles (UAVs) or Drones is increasing exponentially all around the world for a variety of applications. Object tracking using drones has an enormous number of applications, especially in smart transportation system. In this paper, we present a lightweight infrastructure-less object tracking system and assess its performance using the VICON motion capture system. The performance results obtained was very close to that of the optimal infrastructure-based solution.

Original language	English
Title of host publication	2019 IEEE Global Conference on Internet of Things, GCIoT 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728148731
DOIs	https://doi.org/10.1109/GCIoT47977.2019.9058406
Publication status	Published - Nov 2019
Event	2019 IEEE Global Conference on Internet of Things, GCIoT 2019 - Dubai, United Arab Emirates Duration: Dec 4 2019 → Dec 7 2019

Publication series

Name	2019 IEEE Global Conference on Internet of Things, GCIoT 2019

Conference

Conference	2019 IEEE Global Conference on Internet of Things, GCIoT 2019
Country/Territory	United Arab Emirates
City	Dubai
Period	12/4/19 → 12/7/19

Keywords

Cloud computing
Clustering
Energy consumption
Mobile communication
Security
Sensor networks

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Hardware and Architecture
Safety, Risk, Reliability and Quality

Access to Document

10.1109/GCIoT47977.2019.9058406

Cite this

Object Tracking Framework for Unmanned Aerial Vehicles. / Dirir, Ahmed; Elsayed, Hesham.
2019 IEEE Global Conference on Internet of Things, GCIoT 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 9058406 (2019 IEEE Global Conference on Internet of Things, GCIoT 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Dirir, A & Elsayed, H 2019, Object Tracking Framework for Unmanned Aerial Vehicles. in 2019 IEEE Global Conference on Internet of Things, GCIoT 2019., 9058406, 2019 IEEE Global Conference on Internet of Things, GCIoT 2019, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE Global Conference on Internet of Things, GCIoT 2019, Dubai, United Arab Emirates, 12/4/19. https://doi.org/10.1109/GCIoT47977.2019.9058406

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abstract = "Object tracking is a computer vision problem that gained attention in the past few decades. Numerous algorithms targeting various challenges associated with object tracking have been proposed to address issues related to multiple objects tracking, handling complex scenarios like fog and occlusions, and other subproblems within the object tracking area. On the other hand, the extensive use of Unmanned Aerial Vehicles (UAVs) or Drones is increasing exponentially all around the world for a variety of applications. Object tracking using drones has an enormous number of applications, especially in smart transportation system. In this paper, we present a lightweight infrastructure-less object tracking system and assess its performance using the VICON motion capture system. The performance results obtained was very close to that of the optimal infrastructure-based solution.",

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KW - Energy consumption

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KW - Security

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Object Tracking Framework for Unmanned Aerial Vehicles

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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