Скачать или смотреть Visual ego motion estimation in urban environments based on uv disparity

Authors: B Musleh, D Martin, A de la Escalera, JM Armingol

Intelligent Vehicles Symposium (IV), 2012 IEEE, 444-449

The movement of the vehicle provides useful information for different applications, such as driver assistant systems or autonomous vehicles. This information can be known by means of a GPS, but there are some areas in urban environments where the signal is not available, as tunnels or streets with high buildings. A new method for 2D visual ego motion estimation in urban environments is presented in this paper. This method is based on a stereo-vision system where the feature road points are tracked frame to frame in order to estimate the movement of the vehicle, avoiding outliers from
dynamic obstacles. The road profile is used to obtain the world
coordinates of the feature points as a unique function of its left image coordinates. For these reasons it is only necessary
to search feature points in the lower third of the left images.
Moreover, the Kalman filter is used as a solution for filtering
problem. That is, in some cases, it is necessary to filter raw
data due to noise acquisition of time series. The results of the
visual ego motion are compared with raw data from a GPS.