Gait analysis is an examination which extracts objective information from observing human gait and assesses the
function. The equipments used recently for gait analysis are expensive due to multiple cameras and force plates, and
require the large space to set up the system. In this paper, we proposed a method to measure human gait motions in 3D
from a monocular video. Our approach was based on particle filtering to track human motion without training data and
previous information about a gait. We used dynamics to make physics-based motions with the consideration of contacts
between feet and base. In a walking sequence, our approach showed the mean angular error of 12.4° over all joints, which
was much smaller than the error of 34.6° with the conventional particle filter. These results showed that a monocular
camera is able to replace the existing complicated system for measuring human gait quantitatively.