Low-Cost CNN Design for Intelligent Surveillance System

Liang Wei Yang, Chung Yen Su

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In today's world, video surveillance appears everywhere in our life. The challenge for a video surveillance system is to recognize the object of interest for analysis. The convolutional neural network (CNN) models achieve high accuracy on image recognition, but the models require powerful calculations. The models cannot be applied to most smart surveillance systems directly. In this paper, we propose a low-cost CNN design for the application of surveillance systems. Instead of using GPUs, we use a hardware accelerator called Neural Compute Stick (NCS) accompanied with the Rock64 to build the system. The NCS is a low-cost and low-power USB device, which has the advantages in the high-speed calculation of images. As a result, we use the NCS to load the Single Shot MultiBox Detector (SSD) network for human detection. Our system can get each detected image in 0.15 sec. It is six times faster than other single-board surveillance systems. Furthermore, the cost of building the real-time surveillance system is less than 100. Therefore, our system can achieve a low-cost and high-performance intelligent surveillance system.

Original languageEnglish
Title of host publication2018 International Conference on System Science and Engineering, ICSSE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538662854
DOIs
Publication statusPublished - 2018 Nov 1
Event2018 International Conference on System Science and Engineering, ICSSE 2018 - New Taipei City, Taiwan
Duration: 2018 Jun 282018 Jun 30

Publication series

Name2018 International Conference on System Science and Engineering, ICSSE 2018

Conference

Conference2018 International Conference on System Science and Engineering, ICSSE 2018
CountryTaiwan
CityNew Taipei City
Period18/6/2818/6/30

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization

Cite this

Wei Yang, L., & Yen Su, C. (2018). Low-Cost CNN Design for Intelligent Surveillance System. In 2018 International Conference on System Science and Engineering, ICSSE 2018 [8520133] (2018 International Conference on System Science and Engineering, ICSSE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSSE.2018.8520133