Robust Body-Height Estimation for Applications in Automotive Industry

Abstract

An automatic adjustment of the seat position according to the driver height significantly increases the level of comfort when entering a car. A camera attached to a vehicle can estimate the body heights of approaching drivers. However, absolute height estimation based on a single camera leads to several problems. Cost-sensitive cameras used in automotive industry provide low-resolution grayscale images, which make driver extraction in real-life parking scenarios difficult. Absolute height estimation also prerequisites a known camera position relative to a road surface, but this position is not available for any parking scenarios. Toward this, we first propose a background-based driver-extraction method that can operate on low-resolution grayscale images, and that is robust against shadows and illumination changes. Second, we derive a scheme for estimating the camera position relative to an unknown road surface using head and foot points of extracted persons. Our experimental results obtained from real-life video sequences show that the proposed schemes are highly suitable for robust driver extraction and height estimation in automotive industry.