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Real-time categorization of driver's gaze zone and head pose using the convolutional neural network

Authors:

In-Ho Choi,

Thi Bao Hanh Tran,

Yong-Guk KimAuthors Info & Claims

HCIK '16: Proceedings of HCI Korea

Pages 417 - 422

https://doi.org/10.17210/hcik.2016.01.417

Published: 27 January 2016 Publication History

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Abstract

This paper presents categorization of Driver's gaze zone and his head pose estimation using the Convolutional Neural Network (CNN)s. We created a driving database including male, female, glasses and drive career. We divided the gaze zone about face region using CNN and we got a result of more than 95%. Also, we divided a head-pose estimation using CNN and we got a result of less than 5 MAE.

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Index Terms

Real-time categorization of driver's gaze zone and head pose using the convolutional neural network
1. Human-centered computing

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Information & Contributors

Information

Published In

HCIK '16: Proceedings of HCI Korea

January 2016

563 pages

ISBN:9788968487910

General Chairs:
Geehyuk Lee
KAIST, Korea
,
Min Young Choi
Sungshin Women's Univ., Korea
,
Jeongyun Heo
Kookmin Univ., Korea
,
Program Chairs:
Seokhee Jeon
Kyunghee Univ., Korea
,
Nam Choon Park
Seoul Women's Univ., Korea
,
Heokyung Jung
SMIT, Korea

In-Cooperation

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Hanbit Media, Inc.

Seoul, Korea, Republic of

Publication History

Published: 27 January 2016

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HCIK '16 Paper Acceptance Rate 82 of 123 submissions, 67%;

Overall Acceptance Rate 149 of 207 submissions, 72%

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