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Nonparametric approaches for estimating driver pose
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AI
DOI：10.1109/TVT.2007.897634.png)
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摘要
En 中文
To better understand driver behavior, the Federal Highway Administration and the National Highway Traffic Safety Administration have collected several thousands of hours of driver video. There is now an immediate need for devising automated procedures for analyzing the video. In this paper, we look at the problem of estimating driver pose given a video of the driver as he or she drives the vehicle. A complete system is proposed to perform feature extraction and classification of each frame. The system uses a Fisherface representation of video frames and a nearest neighbor and neural network classification scheme. Experimental results show that the system can achieve high accuracy and reliable performance.
Keyword:
classification
driver pose estimation
eigenfaces
fisherfaces
neural networks
video
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期刊
IF:
7.1
论文数:
1.8W
被引数:
6.6W
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