Three Dimensional Change Detection Using Point Clouds: A Review

Change detection is an important step for the characterization of object dynamics at earth’s surface. In multi-temporal point clouds, main challenge to detect true changes different granularities in a scene subject significant noise and occlusion. To better understand new research perspectives this field, deep review recent advances 3D change methods needed. end, we present comprehensive state art approaches, mainly those using clouds. We standard use machine learning detection. addition, paper presents summary cloud benchmark datasets from sensors (aerial, mobile, static), together with associated information. also investigate representative evaluation metrics task. finish, open questions perspectives. By reviewing relevant papers highlight potential bi- clouds monitoring analysis various applications.