Proceeding of the Faculty of technical Sciences, Novi Sad

Mechatronics

Vol. 35 No. 10 (2020): Proceedings of the Faculty of Technical Sciences

JEDNO REŠENJE IMPLEMENTACIJE PROGRAMSKE PODRŠKE ZA PREPOZNAVANJE LICA PRILIKOM PRISTUPA ZAŠTIĆENOJ ZONI

DOI:
https://doi.org/10.24867/09IH01Vukovic
Submitted
February 24, 2020
Published
2020-10-04

Abstract

This paper presents the use of machine vision on embedded platforms using neural networks for face recognition. The paper provides some theoretical insights into the areas used in project development, also demonstrates the implementation and results obtained on embedded platforms Minnowboard, Raspberry Pi and Movidius using the OpenVINO platform.

References

[1] Minnowboard (tehnička dokumentacija), pristup 04.11.2019.preko:(https://minnowboard.org/minnowboard-turbot/technical-specs)
[2] Raspberry Pi (tehnička dokumentacija), pristup 12.07.2019. preko:(https://www.raspberrypi.org/)
[3] Movidius (specifikacije), pristup 04.11.2019. preko:(https://software.intel.com/en-us/neural-compute-stick)
[4]OpenVINO, pristup 14.11.2019. preko: (https://docs.openvinotoolkit.org/)
[5] OpenCV-Python Tutorials Documentation, pristup 04.11.2019.preko:(https://buildmedia.readthedocs.org/media/pdf/opencv-python-tutroals/latest/opencv-python-tutroals.pdf)
[6] FaceNet: A Unified Embedding for Face Recognition and Clustering, pristup 04.11.2019. preko: (https://arxiv.org/abs/1503.03832)
[7] TensorFlow, pristup 04.11.2019, preko:(https://www.tensorflow.org/)
[8] Blockchain, pristup 14.11.2019. preko:(https://en.wikipedia.org/wiki/Blockchain)
[9] Wei-Lun Chao GICE, National Taiwan University, Face Recognition
[10] Deep Neural Network, pristup 14.11.2019. preko:(https://www.techopedia.com/definition/32902/deep-neural-network)
[11] David Habrman, Face Recognition with Preprocessing and Neural Networks, LiTH-ISY-EX--16/4953—SE