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Temporal Motionless Analysis of Video using CNN in MPSoC

Dey, Somdip and Singh, Amit Kumar and Prasad, Dilip Kumar and McDonald-Maier, Klaus (2020) Temporal Motionless Analysis of Video using CNN in MPSoC. In: 2020 IEEE 31st International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2020-07-06 - 2020-07-08, Manchester.

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Abstract

This paper proposes a novel human-inspired methodology called IRON-MAN (Integrated RatiONal prediction and Motionless ANalysis of videos) on 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 of the device.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2020 IEEE 31st International Conference on Application-specific Systems, Architectures and Processors (ASAP)
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 01 Oct 2020 12:04
Last Modified: 01 Oct 2020 12:15
URI: http://repository.essex.ac.uk/id/eprint/28821

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