| Paper Abstract and Keywords |
| Presentation |
2023-09-07 09:50
Improving Performance of Convolutional Neural Network-Based Driver Behavior Recognition
Shengbiao Wang, Koji Iwano (Tokyo City Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
This study investigates the automatic recognition of driver behaviors using images captured by in-vehicle cameras for the purpose of realizing distracted driving detection. While existing methods for behavior recognition utilizing standard convolutional neural networks (CNN) have been explored, their recognition performance has been less than satisfactory. To address this issue, we propose two approaches aimed at improving the performance: (1) the incorporation of an attention mechanism designed to emphasize distinctive regions, and (2) the integration of a neural network utilizing skeleton information extracted by a skeleton detection model as input for behavior recognition, in conjunction with the CNN. Experiments on classification of 10 distinct behaviors using a dataset of approximately 14,000 images from 44 drivers shows that the combined implementation of these two methods improves the accuracy by 3.0 to 6.5%; the maximum recognition accuracy of 86.8% is achieved. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Driver behavior recognition / Image recognition / Convolutional neural network / Attention mechanism / Skeleton information / / / |
| Reference Info. |
ITE Tech. Rep., vol. 47, no. 25, ME2023-90, pp. 7-12, Sept. 2023. |
| Paper # |
ME2023-90 |
| Date of Issue |
2023-08-31 (ME) |
| ISSN |
Online edition: ISSN 2424-1970 |
| Download PDF |
|
| Conference Information |
| Committee |
ME IEICE-EMM IEICE-IE IEICE-LOIS IEE-CMN IPSJ-AVM |
| Conference Date |
2023-09-07 - 2023-09-07 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Osaka Metropolitan Univ. |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
|
| Paper Information |
| Registration To |
ME |
| Conference Code |
2023-09-ME-EMM-IE-LOIS-CMN-AVM |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Improving Performance of Convolutional Neural Network-Based Driver Behavior Recognition |
| Sub Title (in English) |
|
| Keyword(1) |
Driver behavior recognition |
| Keyword(2) |
Image recognition |
| Keyword(3) |
Convolutional neural network |
| Keyword(4) |
Attention mechanism |
| Keyword(5) |
Skeleton information |
| Keyword(6) |
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| Keyword(7) |
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| 1st Author's Name |
Shengbiao Wang |
| 1st Author's Affiliation |
Tokyo City University (Tokyo City Univ.) |
| 2nd Author's Name |
Koji Iwano |
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Tokyo City University (Tokyo City Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2023-09-07 09:50:00 |
| Presentation Time |
20 minutes |
| Registration for |
ME |
| Paper # |
ME2023-90 |
| Volume (vol) |
vol.47 |
| Number (no) |
no.25 |
| Page |
pp.7-12 |
| #Pages |
6 |
| Date of Issue |
2023-08-31 (ME) |