TY - CONF T1 - Pedestrian classification from moving platforms using cyclic motion pattern T2 - IEEE International Conference on Image Processing, 2005. ICIP 2005 Y1 - 2005 A1 - Yang Ran A1 - Qinfen Zheng A1 - Weiss, I. A1 - Davis, Larry S. A1 - Abd-Almageed, Wael A1 - Liang Zhao KW - compact shape representation KW - cyclic motion pattern KW - data mining KW - Detectors KW - digital phase locked loop KW - digital phase locked loops KW - feedback loop module KW - gait analysis KW - gait phase information KW - human body pixel oscillations KW - HUMANS KW - image classification KW - Image motion analysis KW - image representation KW - image sequence KW - Image sequences KW - Motion detection KW - Object detection KW - pedestrian classification KW - pedestrian detection system KW - Phase estimation KW - Phase locked loops KW - principle gait angle KW - SHAPE KW - tracking KW - Videos AB - 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. JA - IEEE International Conference on Image Processing, 2005. ICIP 2005 PB - IEEE VL - 2 SN - 0-7803-9134-9 M3 - 10.1109/ICIP.2005.1530190 ER -