Egomotion Estimation in Monocular Infra-red Image Sequence for Night Vision Applications

This paper presents a real-time egomotion estimation scheme that is specifically designed for measuring vehicle motion from a monocular infra-red image sequence at night time. Conventional methods of estimating camera motion such as optical-flow based method or direct-method that depends on brightness constancy do not work well in relatively low resolution infra-red imagery due to lack of textureness. In this paper, we propose a method that is based on aggregate feature tracking that is constrained by focus of expansion from instantaneous vehicle motion. Qualitative analysis of error is presented by comparing with groundtruth accelerometer data. An application of ground plane estimation combined with vanishing point estimation is also presented for robust pose estimation