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概要（英語）
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For the purpose of preventing and deterring crime, surveillance is carried out across various fields, such as companies and government, by deploying security guards and cameras. However, as the monitoring area expands the costs employing security guard increases. Therefore, the automation of monitoring is being implemented as a solution to alleviate the burden on security guards. To achieve this, a mechanism for identifying people is necessary. Cameras are commonly used for personal identification, but methods that use cameras can be invasive of privacy and may not be deployable in certain locations. Therefore, in this paper, we propose a method for extracting features useful for personal identification using 2D LiDAR, aiming to develop a personal identification system that addresses the drawbacks of cameras. By using 2D LiDAR, a person's movement within the measurement area is detected, and gait features are extracted as characteristics for personal identification. We confirmed that it is possible to estimate person by gait features obtained from 2D LiDAR.
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