By Topic

Turn-Intent Analysis Using Body Pose for Intelligent Driver Assistance

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Shinko Yuanhsien Cheng ; University of California, San Diego ; M. M. Trivedi

Human-centric, pervasive computing environments, with integrated sensing, processing, networking, and displays, provide an appropriate framework for developing effective driver-assistance systems. Also essential when developing such systems are systematic efforts to understand and characterize driver behavior. In an attempt to make such a predictive turn-assistance safety system a reality, we equipped an experimental vehicle with cameras and sensors to capture the vehicle dynamics, view of the road ahead, and driver's body pose. We investigated how and to what extent we could use body-pose information to detect and predict driver activities. We analyzed the detection performance of a two-class pattern classifier using receiver-operator-characteristic curves, which describe the classifier's ability to suppress missed detections and false alarms. The curves provide a ratio indicating the system's attainable proactivity (ability to foresee a user's needs) versus its transparency (ability to avoid user annoyance). Our goal is to eventually develop vision-based body-pose-recovery and behavior-recognition algorithms for driver-assistance systems

Published in:

IEEE Pervasive Computing  (Volume:5 ,  Issue: 4 )