Dey, Somdip and Singh, Amit Kumar and Prasad, Dilip Kumar and McDonald-Maier, Klaus (2020) 'IRON-MAN: An Approach To Perform Temporal Motionless Analysis of Video using CNN in MPSoC.' IEEE Access, 8. pp. 137101-137115. ISSN 2169-3536

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Abstract

This paper proposes a novel human-inspired methodology called IRON-MAN ( Integrated RatiONal prediction and Motionless ANalysis ) for mobile multi-processor systems-on-chips (MPSoCs). The methodology integrates analysis of the previous image frames of the video to represent the analysis of the current frame in order to perform Temporal Motionless Analysis of the Video ( TMAV ). This is the first work on TMAV using Convolutional Neural Network (CNN) for scene prediction in MPSoCs. Experimental results show that our methodology outperforms state-of-the-art. We also introduce a metric named, Energy Consumption per Training Image ( ECTI ) to assess the suitability of using a CNN model in mobile MPSoCs with a focus on energy consumption and lifespan reliability of the device.

Item Type:	Article
Uncontrolled Keywords:	Streaming media; Predictive models; Cameras; Energy consumption; Reliability; Analytical models; Convolutional neural networks; Convolutional neural network (CNN); temporal analysis; motionless analysis; video; lifespan; energy efficiency; embedded device; multiprocessor systems-on-chip (MPSoCs)
Divisions:	Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor:	Elements
Depositing User:	Elements
Date Deposited:	13 Aug 2020 14:17
Last Modified:	15 Jan 2022 01:34
URI:	http://repository.essex.ac.uk/id/eprint/28341

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