In this paper, the authors describe a novel image-based person identification task. Traditional face-based person identification methods have a low tolerance for occluded situation, such as overlapping of people in an image. The authors focus on an image from an overhead camera. The authors utilize depth information for the identification task. By using depth information, the authors can capture the precise person\u2019s area and rich information for the identification task as compared with popular RGB cameras. The authors apply four features extracted from images based on depth information to the identification method; (1) estimated body height, (2) estimated body dimensions, (3) estimated body size and (4) depth histogram. In the experiment, the authors evaluated two situations; (a) standing in front of a door and (b) touching a doorknob. The identification accuracy rates are 94.4% and 91.4% on the two situations. 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