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Monitoring Driver's Cognitive Status Based on Integration of Internal and External Information

Published: 21 October 2015 Publication History

Abstract

In Advanced Driving Assistance Systems (ADASs), monitoring the driver's cognitive status during driving is considered as an important issue. Because, most of the accidents in the automotive sector occur due to the driver's misinterpretation or lack of sufficient information regarding the situation. In order to prevent these accidents, current ADASs include lane departure warning systems, vehicle detection systems, advanced cruise control systems, etc. In a particular driving scenario, the amount of information available to the driver regarding a situation can be judged by monitoring the driver's gaze (internal information) and distributions corresponding to the forward traffic (external information). Therefore, to provide sufficient information to the driver regarding a driving scenario it is essential to integrate the internal and external information which is lacking in the current ADASs. In this paper, we use 3D pose estimate algorithm (POSIT) to estimate driver's attention area. In order to estimate the distributions corresponding to the forward traffic we employ Bottom-up Saliency map. To integrate the internal and external information we use conditional mutual information.

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  1. Monitoring Driver's Cognitive Status Based on Integration of Internal and External Information

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    HAI '15: Proceedings of the 3rd International Conference on Human-Agent Interaction
    October 2015
    254 pages
    ISBN:9781450335270
    DOI:10.1145/2814940
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    • BESK: Brain Engineering Society of Korea

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 21 October 2015

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    Author Tags

    1. ADAS system
    2. gestalt saliency map
    3. head pose estimate
    4. mutual information

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    • Research-article

    Funding Sources

    • This research was supported by the MSIP(Ministry of Science ICT and Future Planning) Korea under the C-ITRC(Convergence Infor
    • The research was supported by 'Software Convergence Technology Development Program' through the Ministry of Science ICT and Fu

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    HAI 2015
    Sponsor:
    • BESK
    HAI 2015: The Third International Conference on Human-Agent Interaction
    October 21 - 24, 2015
    Kyungpook, Daegu, Republic of Korea

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    Overall Acceptance Rate 121 of 404 submissions, 30%

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