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A Performance of Low-Cost NVIDIA Jetson Nano Embedded System in the Real-Time Siamese Single Object Tracking: A Comparison Study

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Computing Science, Communication and Security (COMS2 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1604))

Abstract

The tracking of objects is a complex mission computer vision and machine learning (ML). There are several types of objects tracking like tracking one object or more than one. The tracking of one object is applied in video frames as the tracking of more than one object is applied to tracking for multiple objects in the video. Single object tracking is usually implemented using the method of correlation filter-based or of Siamese Network-based. Siamese Network, the state of art method, has an active search area, nowadays, due to its good achievements in accordance with localization real-time and accuracy application. Especially within a new surveillance system that is built on UAV to get unbounded tracking. GPU-based embedded systems give superior performance in comparison with CPU-based systems in the implementation of ML in the terms of speed. In this paper low-cost NVIDIA Jetson nano embedded system performance was evaluated for real-time Siamese single object tracking. 14 Siamese single object tracking algorithms were tested using NVIDIA Jetson nano board. The result shows that the bord gives the best performance with the Lighttrack algorithm with 8.3 frames per second speed. Such performance can be used in real-time tracking applications.

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Authors and Affiliations

  1. Electrical Engineering Technical College, Department of Computer Technical Engineering, Middle Technical University (MTU), Al Doura, 10022, Baghdad, Iraq

    Abbas Aqeel Kareem & Dalal Abdulmohsin Hammood

  2. Computer Techniques Engineering Department, Dijlah University College, Baghdad, Iraq

    Ahmed A. Alchalaby

  3. Institute of Technology, ICT Department, Middle Technical University, Baghdad, Iraq

    Ruaa Ali Khamees

Authors
  1. Abbas Aqeel Kareem
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  2. Dalal Abdulmohsin Hammood
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  3. Ahmed A. Alchalaby
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  4. Ruaa Ali Khamees
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Corresponding author

Correspondence to Dalal Abdulmohsin Hammood .

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Editors and Affiliations

  1. Ganpat University, Gujarat, India

    Nirbhay Chaubey

  2. IIITM-Kerala, Trivandrum, India

    Sabu M. Thampi

  3. Taylor's University, Subang Jaya, Malaysia

    Noor Zaman Jhanjhi

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Kareem, A.A., Hammood, D.A., Alchalaby, A.A., Khamees, R.A. (2022). A Performance of Low-Cost NVIDIA Jetson Nano Embedded System in the Real-Time Siamese Single Object Tracking: A Comparison Study. In: Chaubey, N., Thampi, S.M., Jhanjhi, N.Z. (eds) Computing Science, Communication and Security. COMS2 2022. Communications in Computer and Information Science, vol 1604. Springer, Cham. https://doi.org/10.1007/978-3-031-10551-7_22

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  • DOI: https://doi.org/10.1007/978-3-031-10551-7_22

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