Abstract
This article discusses feasibility of detecting mislay of objects when they are left by users from their behavior. From questionnaires to the participants for the videos with mislay of objects, it has been found that time passed after the most recent manipulation of objects as well as number of objects left after being brought to the place serve as useful clues to detect mislay of objects. Since those clues can be obtained from videos using conventional methods of human pose estimation and object recognition, it is also shown that mislay of objects can be automatically detected from the videos.
