Estimation of pedestrian walking direction from video

In this paper we study 3D pedestrian motion direction estimation using a projective geometry based method. The idea for estimation is based on image sequence analysis, where the detection of both head and toe points will provide measurements for vanishing point estimation. Knowing that once the walk direction is fixed, these two points move along 3D parallel lines. This estimation assumes that there is a binary segmentation of the pedestrian. For each frame, the top and the bottom points of the segmentation are extracted. One line is fitted to the collection of top points and the other to the collection of the bottom points. Given these two lines, the vanishing point is estimated and thence the direction of the pedestrian. Our approach either assumes two intrinsic parameters cameras that are known or estimated at a learning stage using two previously known walking pedestrian directions. Experiments using a publicly available database show an accurate estimation of the direction of the body with less than 3 degrees error.