TechRxiv
conference_041818.pdf (502.83 kB)

Temporal Motionless Analysis of Video using CNN in MPSoC

Download (502.83 kB)
preprint
posted on 20.07.2020 by Somdip Dey, Amit Singh, Dilip Kumar Prasad, Klaus D. Mcdonald-Maier

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.

Funding

National Centre for Nuclear Robotics (NCNR)

Engineering and Physical Sciences Research Council

Find out more...

Robust remote sensing for multi-modal characterisation in nuclear and other extreme environments

Engineering and Physical Sciences Research Council

Find out more...

History

Email Address of Submitting Author

somdip.dey@essex.ac.uk

ORCID of Submitting Author

0000-0001-6161-4637

Submitting Author's Institution

University of Essex

Submitting Author's Country

United Kingdom

Licence

Exports