Human motion description and recognition under arbitrary motion direction
Youtaro Yamashita, Joo Kooi Tan, Seiji Ishikawa · 2017
According to the increase in the number of elderly people living alone, nursing care systems for such people have become much more important than ever. This paper focuses its attention on the detection of abnormal motions such as falling of the elderly by use of a camera settled in a room. Although there are several human motion representation and recognition methods, they all deal with the motions acted in a plane perpendicular to camera view, which suggests weakness of their motion description method. This paper proposes a novel method of describing a human motion independent of motion direction. The method expands the original 2-D Motion History Image to a 3-D version and computes the Hu moments in a 3-D way for the motion recognition. The method as well proposes a set of three 2-D images for motion description derived from the 3D-MHI to reduce computational load. The performance of the proposed method is shown experimentally and discussion is given.