%0 Conference Paper %B IEEE International Conference on Image Processing, 2005. ICIP 2005 %D 2005 %T Pedestrian classification from moving platforms using cyclic motion pattern %A Yang Ran %A Qinfen Zheng %A Weiss, I. %A Davis, Larry S. %A Abd-Almageed, Wael %A Liang Zhao %K compact shape representation %K cyclic motion pattern %K data mining %K Detectors %K digital phase locked loop %K digital phase locked loops %K feedback loop module %K gait analysis %K gait phase information %K human body pixel oscillations %K HUMANS %K image classification %K Image motion analysis %K image representation %K image sequence %K Image sequences %K Motion detection %K Object detection %K pedestrian classification %K pedestrian detection system %K Phase estimation %K Phase locked loops %K principle gait angle %K SHAPE %K tracking %K Videos %X This paper describes an efficient pedestrian detection system for videos acquired from moving platforms. Given a detected and tracked object as a sequence of images within a bounding box, we describe the periodic signature of its motion pattern using a twin-pendulum model. Then a principle gait angle is extracted in every frame providing gait phase information. By estimating the periodicity from the phase data using a digital phase locked loop (dPLL), we quantify the cyclic pattern of the object, which helps us to continuously classify it as a pedestrian. Past approaches have used shape detectors applied to a single image or classifiers based on human body pixel oscillations, but ours is the first to integrate a global cyclic motion model and periodicity analysis. Novel contributions of this paper include: i) development of a compact shape representation of cyclic motion as a signature for a pedestrian, ii) estimation of gait period via a feedback loop module, and iii) implementation of a fast online pedestrian classification system which operates on videos acquired from moving platforms. %B IEEE International Conference on Image Processing, 2005. ICIP 2005 %I IEEE %V 2 %P II- 854-7 - II- 854-7 %8 2005/09// %@ 0-7803-9134-9 %G eng %R 10.1109/ICIP.2005.1530190