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On Restricted Computational Systems, Real-time Multi-tracking and Object Recognition Tasks are Possible
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0001-6158-3543
Department of Computer Engineering, Asia Pacific University, Kuala Lumpur, Malaysia.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0003-1343-1742
Department of Physics, City University of Hong Kong, Hong Kong.
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2022 (English)In: 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), IEEE , 2022, p. 1523-1528Conference paper, Published paper (Refereed)
Abstract [en]

Intelligent surveillance systems are inherently computationally intensive. And with their ever-expanding utilization in both small-scale home security applications and on the national scale, the necessity for efficient computer vision processing is critical. To this end, we propose a framework that utilizes modern hardware by incorporating multi-threading and concurrency to facilitate the complex processes associated with object detection, tracking, and identification, enabling lower-powered systems to support such intelligent surveillance systems effectively. The proposed architecture provides an adaptable and robust processing pipeline, leveraging the thread pool design pattern. The developed method can achieve respectable throughput rates on low-powered or constrained compute platforms.

Place, publisher, year, edition, pages
IEEE , 2022. p. 1523-1528
Keywords [en]
object tracking, optimization, Scalable intelligent surveillance system
National Category
Computer Sciences
Research subject
Machine Learning
Identifiers
URN: urn:nbn:se:ltu:diva-95534DOI: 10.1109/IEEM55944.2022.9989755Scopus ID: 2-s2.0-85146357090ISBN: 978-1-6654-8687-3 (electronic)OAI: oai:DiVA.org:ltu-95534DiVA, id: diva2:1734991
Conference
2022 Engineering and Engineering Management (IEEM 2022), December 7-10 2022, Kuala Lumpur, Malaysia
Available from: 2023-02-07 Created: 2023-02-07 Last updated: 2023-09-05Bibliographically approved

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Mokayed, HamamAlkhaled, Lama

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