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In this paper, a method for automatic pedestrian detection from monocular image sequence is described. It discriminates the pedestrians from the other moving objects based on the rhythmical motion of human walking. When both feet of a pedestrian are on the ground in walking, their motions are found to have a relatively small changes of intensity in subtracted image. When one of the feet is moving forward, its motion is found to have a relatively large changes of intensity. Therefore, the periodical changing of image intensity caused by walking can be observed by applying the maximum entropy method. The state of a moving object, such as position and velocity, can be estimated with a kinematic model, a measurement model and a tracking filter. Corresponding to the pace and the 1/stride of walking, the rhythm is decomposed into two features; the temporal-frequency and the spatial-frequency. The model matching is performed based on these features.>
Yasutomi et al. (Tue,) studied this question.
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