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SUMMARYIt is important for mobile robots and security purposes to discriminate a pedestrian among moving objects in a video. This paper proposes a method which discriminates a pedestrian from other objects by using periodic motions of the feet, and the characteristics of the rhythm of pace and stride. This method uses brightness changes in sequential images of a moving object contacting with the ground, and extracts the main component of the frequency using a power spectrum estimation. Therefore, the method is independent of pedestrian's appearance such as clothes, build, and hair style. The system realizing this method consists of three processes: moving object detection which uses the difference between successive image frames; tracking of the moving object using a moving model with an extended Kalman filter and an observation model; and detection of the pedestrian based on rhythm of walking using the difference of brightness between images on successive frames. The whole process is performed in real time. Experiments using real scenes confirm the effectiveness of the proposed method: 446 pedestrians out of 470 were successfully detected (detection rate 94.9%), and 101 persons out of 106 were successfully detected as non-pedestrians (96.2%).

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