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Human Motion Blending by Using the Markers of Motion
Capture as Clusters
Jung-Ying Wang 1* Tsung-Han Tu 2 Fang-Cheng Hsu 3
1, 3
Department of Multimedia and Game Science Lunghwa University of Science and Technology, Taiwan
2
Department of Electronic Engineering Lunghwa University, Taiwan *E-mail: wyy@mail.lhu.edu.tw
Abstract
In this paper we present a general method for motion blending that could be used to smoothly blend two motion clips and could automatically select the transition key frames. Animators can use this approach to produce a new move sequence. The main contribution of our study is that we directly utilize the amount of makers in motion capture equipment as the clusters in clustering method to avoid the drawback of assigning the thresholds of fuzzy clusters by hand. In order to simplify and accelerate the efficiency of motion blending, each motion clip is selected only one frame, as the key frame, to represent all time frames of that motion. This key frame retains the important characteristic of that motion clip. We use the characteristics of k-mean clustering algorithm to find out the key frame of each motion clip. After that, we do the motion blending by linear interpolation between the two representational key frames. We also use the 4 stages of linear interpolation to replace the time wrapping process. To evaluate the effectiveness of the proposed method, we implemented a series of action mixed experiments. The results show that our method is effective in smoothly blending between two motion sequences.
Keywords: Motion capture, Motion blending, Clustering, linear interpolation
Human Motion Blending by Using the Markers of Motion
Capture as Clusters
Jung-Ying Wang 1* Tsung-Han Tu 2 Fang-Cheng Hsu 3
1, 3
Department of Multimedia and Game Science Lunghwa University of Science and Technology, Taiwan
2
Department of Electronic Engineering Lunghwa University, Taiwan *E-mail: wyy@mail.lhu.edu.tw
Abstract
In this paper we present a general method for motion blending that could be used to smoothly blend two motion clips and could automatically select the transition key frames. Animators can use this approach to produce a new move sequence. The main contribution of our study is that we directly utilize the amount of makers in motion capture equipment as the clusters in clustering method to avoid the drawback of assigning the thresholds of fuzzy clusters by hand. In order to simplify and accelerate the efficiency of motion blending, each motion clip is selected only one frame, as the key frame, to represent all time frames of that motion. This key frame retains the important characteristic of that motion clip. We use the characteristics of k-mean clustering algorithm to find out the key frame of each motion clip. After that, we do the motion blending by linear interpolation between the two representational key frames. We also use the 4 stages of linear interpolation to replace the time wrapping process. To evaluate the effectiveness of the proposed method, we implemented a series of action mixed experiments. The results show that our method is effective in smoothly blending between two motion sequences.
Keywords: Motion capture, Motion blending, Clustering, linear interpolation
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