2 research outputs found
A Method of Describing a Self-occlusive Motion - A Reverse Motion History Image
This paper proposes a new method of describing a self-occlusive human motion, particularly in the depth direction, which has been considered little in the motion/action recognition studies to date in spite of its importance in our daily life. A Motion History Image (MHI) is a well-known method of describing a motion by a single gray value image, but it suffers from a self-occlusion problem in which present motion overwrites past motion. To solve this difficulty, a Reverse description MHI (RMHI) is proposed in the paper. RMHI and the original MHI are both employed for motion representation in the proposed method; the former for approach motion, whereas the latter for leave motion. In the experiment on motion recognition, motions are described by RMHI or MHI according to motion direction, transformed then to Hu moment vectors, and finally recognized employing the k-nearest neighbor. Experimental results show effectiveness of the RMHI description
A Method of Describing a Self-occlusive Motion - A Reverse Motion History Image
This paper proposes a new method of describing a self-occlusive human motion, particularly in the depth direction, which has been considered little in the motion/action recognition studies to date in spite of its importance in our daily life. A Motion History Image (MHI) is a well-known method of describing a motion by a single gray value image, but it suffers from a self-occlusion problem in which present motion overwrites past motion. To solve this difficulty, a Reverse description MHI (RMHI) is proposed in the paper. RMHI and the original MHI are both employed for motion representation in the proposed method; the former for approach motion, whereas the latter for leave motion. In the experiment on motion recognition, motions are described by RMHI or MHI according to motion direction, transformed then to Hu moment vectors, and finally recognized employing the k-nearest neighbor. Experimental results show effectiveness of the RMHI description