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s Recently we daily use the global positioning systems for obtaining the location for car navigation. These systems are very convenient for driving, but we sometimes need more accurate system for obtaining the locations of the specified objects like sports athletes, and also may demand for the location estimation in the indoor environments for obtaining the(More)
—We study the problem of analyzing and classifying frontal view gait video data. In this study, we suppose that frontal view gait data as a mixing of scale changing, human movements and speed changing parameters. We estimate these parameters using the statistical registration and modeling on a video data. Our gait model is based on human gait structure and(More)
—We study the problem of analyzing indoor location estimation by statistical radial distribution model. In this study, we suppose the observed distance data between transmitter and receiver as a statistical radial distribution. The proposed method is based on the marginal likelihoods of radial distribution generated by positive distribution among the(More)
—Recently, the study with microwave Doppler radar is paid attention to. Microwave Doppler radar is one of the non-contact sensor, and detects the action of objects. The study focused on indoor human behavior has been developed. However, disturbance environment that pet and electronic device are moving in the room is considered in real daily life. We(More)
We study the problem of analyzing indoor location estimation by statistical radial distribution model. In this study, we suppose the observed distance data between transmitter and receiver as a radial log-normal distribution. We estimate the subject's location using marginal likelihoods of radial lognormal distribution. To demonstrate the effectiveness of(More)
—We study the problem of analyzing and classifying frontal view gait video data. In this study, we suppose that frontal view gait data as a mixing of scale changing, human movements and speed changing parameters. We estimate these parameters using the statistical registration and modeling on a video data. Our gait model is based on human gait structure and(More)
—We study the problem of analyzing and classifying frontal view gait video data. In this study, we suppose that frontal view gait data as a mixing of scale changing, human movements and speed changing parameters. We estimate these parameters using the statistical registration and modeling on a video data. To demonstrate the effectiveness of our method, we(More)
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