Pedestrian Tracking from a Moving Host Using Corner Points

• Published in: Advances in Visual Computing Vol. 4842; pp. 367 - 376
• Main Authors: Meuter, Mirko, Müller, Dennis, Müller-Schneiders, Stefan, Iurgel, Uri, Park, Su-Birm, Kummert, Anton
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2007; Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Artificial intelligence; Corner Point; Correction Step; Image processing; Interest Point; Pattern recognition; Point Trajectory; Search Region
• ISBN: 9783540768555; 3540768556
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-76856-2_36

We present a new camera based algorithm to track pedestrians from a moving host using corner points. The algorithm can handle partial shape variations and the set of point movement vectors allows to estimate not only translation but also scaling. The algorithm works as follows: Corner points are extracted within a bounding box, where the pedestrian is detected in the current frame and in a search region in the next frame. We compare the local neighbourhood of points to find point correspondences using an improved method. The point correspondences are used to estimate the object movement using a translation scale model. A fast iterative outlier removal strategy is employed to remove single false point matches. A correction step is presented to correct the position estimate. The step uses the accumulated movement of each point over time to detect outliers that can not be found using inter-frame motion vectors. First tests indicate a good performance of the presented tracking algorithm, which is improved by the presented correction step.