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Conference Paper
Study on Training Convolutional Neural Network to Detect Distraction and Drowsiness
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- Authors
- Whui Kim, Hyun-Kyun Choi, Byung-Tae Jang
- Issue Date
- 2018-07
- Citation
- IEEE Region 10 Symposium (TENSYMP) 2018, pp.253-257
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Most critical reason of the crash causal chain was caused by the driver. In other to reduce such human factors, it is necessary to use multiple pieces of information acquired by monitoring driver. In this paper, we propose a method to detect both distraction and drowsiness using a single convolutional neural network, and show that data composition should be different depending on the relationship of two or more class properties. In our experiments, we show driver distraction and drowsiness are reliably classified without decreasing accuracy and frames per seconds.
- KSP Keywords
- Convolution neural network(CNN), Driver distraction, Human Factors, causal chain