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The Study of Driver Fatigue Monitor Algorithm Combined PERCLOS and AECS

Authors: Liying Lang; Haoxiang Qi;

The Study of Driver Fatigue Monitor Algorithm Combined PERCLOS and AECS

Abstract

In this paper, combined PERCLOS and AECS, we introduce an algorithm to detect the driver fatigue. The algorithm, based on color image skin color segment, can directly transforms the RGB form image to the gradation image by the skin color segmentation, and then the eyes is detected. Then we identify eyepsilas condition through the judgment of eye area. Finally, this driver fatigue monitor algorithm calculates the speed of eye close at a short time.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Top 10%
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