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Inventi Impact - Vehicular Technology

Articles

  • Inventi:evt/64/14
    DRIVING POSTURE RECOGNITION BY JOINT APPLICATION OF MOTION HISTORY IMAGE AND PYRAMID HISTOGRAM OF ORIENTED GRADIENTS
    Chao Yan, Frans Coenen, Bailing Zhang

    In the field of intelligent transportation system (ITS), automatic interpretation of a driver’s behavior is an urgent and challenging topic. This paper studies vision-based driving posture recognition in the human action recognition framework. A driving action dataset was prepared by a side-mounted camera looking at a driver’s left profile.The driving actions, including operating the shift lever, talking on a cell phone, eating, and smoking, are first decomposed into a number of predefined action primitives, that is, interaction with shift lever, operating the shift lever, interaction with head, and interaction with dashboard. A global grid-based representation for the action primitives was emphasized, which first generate the silhouette shape from motion history image, followed by application of the pyramid histogram of oriented gradients (PHOG) for more discriminating characterization. The randomforest (RF) classifier was then exploited to classify the action primitives together with comparisons to some other commonly applied classifiers such as ??NN, multiple layer perceptron, and support vector machine. Classification accuracy is over 94% for the RF classifier in holdout and cross-validation experiments on the four manually decomposed driving actions.

    How to Cite this Article
    CC Compliant Citation: Chao Yan, Frans Coenen, and Bailing Zhang, “Driving Posture Recognition by Joint Application of Motion History Image and Pyramid Histogram of Oriented Gradients,” International Journal of Vehicular Technology, vol. 2014, Article ID 719413, 11 pages, 2014. doi:10.1155/2014/719413. Copyright © 2014 Chao Yan et al. This is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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