HyHope: Hybrid Head Orientation and Position Estimation
Driver distraction and inattention are prominent causes of automotive collisions. To
enable driver assistance systems to address these problems, we require new sensing
approaches to infer a driver's focus of attention. In this paper, we present a new 3D
tracking algorithm and integrate it into HyHOPE, a real-time (30fps) Hybrid Head Orientation
and Position Estmation system for driver head tracking. With a single video camera, the
system continuously tracks the head in six degrees-of-freedom, initializing itself
automatically with separate modules for head detection and head pose estimation. The
tracking module provides a fine estimate of the 3D motion of the head, using a new
appearance-based algorithm for 3Dmodel tracking by particle filtering in an augmented
reality environment. We describe our implementation, which utilizes OpenGL-optimized
graphics hardware to efficiently compute particle samples in real-time. To quantitatively
evaluate the accuracy of our system, we compare its estimation results to a marker-based
cinematic motion capture system installed in an automotive testbed. We evaluate the system
on real daytime and nighttime drives with drivers of varying ages, race, and sex.
