Real-time embedded intelligence system : emotion recognition on Raspberry Pi with Intel NCS

Xing, Y and Kirkland, P and Di Caterina, G and Soraghan, J and Matich, G (2018) Real-time embedded intelligence system : emotion recognition on Raspberry Pi with Intel NCS. In: 27th International Conference on Artificial Neural Networks, 2018-10-05 - 2018-10-07. (https://doi.org/10.1007/978-3-030-01418-6_78)

[thumbnail of Xing-etal-ICANN2018-Real-time-embedded-intelligence-system]
Preview
 Text. Filename: Xing_etal_ICANN2018_Real_time_embedded_intelligence_system.pdf
Accepted Author Manuscript
Download (379kB)| Preview

Abstract

Convolutional Neural Networks (CNNs) have exhibited certain human-like performance on computer vision related tasks. Over the past few years since they have outperformed conventional algorithms in a range of image processing problems. However, to utilise a CNN model with millions of free parameters on a source limited embedded system is a challenging problem. The Intel Neural Compute Stick (NCS) provides a possible route for running largescale neural networks on a low cost, low power, portable unit. In this paper, we propose a CNN based Raspberry Pi system that can run a pre-trained inference model in real time with an average power consumption of 6.2W. The Intel Movidius NCS, which avoids requirements of expensive processing units e.g. GPU, FPGA. The system is demonstrated using a facial image-based emotion recogniser. A fine-tuned CNN model is designed and trained to perform inference on each captured frame within the processing modules of NCS.

CORE (COnnecting REpositories)