Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)

Research on Face Recognition of Large Capacity Coherent Photoelectric Hybrid

Authors
Yan-min Zhou, Jian-fang Li
Corresponding Author
Yan-min Zhou
Available Online April 2017.
DOI
https://doi.org/10.2991/fmsmt-17.2017.15How to use a DOI?
Keywords
Large Capacity Coherent Light; Face Recognition; Photoelectric Mixing
Abstract
With the increase of the face database, the electronic computing is exponentially increasing, and the traditional face recognition method can't meet the requirement of real-time recognition. Optical actuator have parallel processing, fast features, and thus in the face recognition side and presents a huge potential. The application of photoelectric hybrid processing system in face recognition should not only follow the common law of ordinary photoelectric hybrid processing system, but also play the advantages of light calculation. The application of photoelectric hybrid processing system in human visual target recognition is to follow the common law of ordinary photoelectric hybrid processing system, but also take into account the special needs of human visual application, so its feasibility study status, research level, photoelectric hybrid processing A large number of studies selected to improve the innovation suitable for robot vision recognition hardware structure and software algorithms and other issues to explore the issue.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Yan-min Zhou
AU  - Jian-fang Li
PY  - 2017/04
DA  - 2017/04
TI  - Research on Face Recognition of Large Capacity Coherent Photoelectric Hybrid
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 73
EP  - 76
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.15
DO  - https://doi.org/10.2991/fmsmt-17.2017.15
ID  - Zhou2017/04
ER  -