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.