Optical flow measurement of human walking

Abstract

This paper presents a method for using optical flow measurements to estimate stride length for pedestrian navigation applications. Optical flow sensors, such as the detectors used in an optical computer mouse, measure the velocity of visual features traversing an imaging array. We consider the case in which the optical flow sensor is attached to the leg of a pedestrian and used to infer distance traveled. In this configuration, optical flow data are a projection of the velocity and angular velocity of the leg to which the sensor is attached; a dynamic motion model is needed to estimate leg states and to infer stride length from the optical flow data. In this paper, we consider a very simple dynamic walking model, called the Spring Loaded Inverted Pendulum (SLIP) model. In a hardware-based trial, the basic SLIP model estimated stride length with 10% error. We anticipate that refinements to the basic SLIP model will enable more accurate stride-length estimation in the future.