Abstract
ABSTRACT This study proposes an indoor movable static object extraction approach for building environmental maps that describe indoor human activities. In particular, it is essential to distinguishing people from non-human movable objects. To address this issue, we classify static objects into three categories based on their features. Methods for extracting movable static objects using each feature are presented. We conducted experiments and confirmed that the movable static objects were successfully detected and redefined as backgrounds, and only people were determined as dynamic objects.
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