  Video and wearable sensor data provide complementary information about human
movement. Video provides a holistic understanding of the entire body in the
world while wearable sensors provide high-resolution measurements of specific
body segments. A robust method to fuse these modalities and obtain
biomechanically accurate kinematics would have substantial utility for clinical
assessment and monitoring. While multiple video-sensor fusion methods exist,
most assume that a time-intensive, and often brittle, sensor-body calibration
process has already been performed. In this work, we present a method to
combine handheld smartphone video and uncalibrated wearable sensor data at
their full temporal resolution. Our monocular, video-only, biomechanical
reconstruction already performs well, with only several degrees of error at the
knee during walking compared to markerless motion capture. Reconstructing from
a fusion of video and wearable sensor data further reduces this error. We
validate this in a mixture of people with no gait impairments, lower limb
prosthesis users, and individuals with a history of stroke. We also show that
sensor data allows tracking through periods of visual occlusion.
