Abstract
This paper presents a method of reconstructing full-body locomotion sequences for virtual characters in real-time, using data from a single inertial measurement unit (IMU). This process can be characterized by its difficulty because of the need to reconstruct a high number of degrees of freedom (DOFs) from a very low number of DOFs. To solve such a complex problem, the presented method is divided into several steps. The user’s full-body locomotion and the IMU’s data are recorded simultaneously. Then, the data is preprocessed in such a way that would be handled more efficiently. By developing a hierarchical multivariate hidden Markov model with reactive interpolation functionality the system learns the structure of the motion sequences. Specifically, the phases of the locomotion sequence are assigned in the higher hierarchical level, and the frame structure of the motion sequences are assigned at the lower hierarchical level. During the runtime of the method, the forward algorithm is used for reconstructing the full-body motion of a virtual character. Firstly, the method predicts the phase where the input motion belongs (higher hierarchical level). Secondly, the method predicts the closest trajectories and their progression and interpolates the most probable of them to reconstruct the virtual character’s full-body motion (lower hierarchical level). Evaluating the proposed method shows that it works on reasonable framerates and minimizes the reconstruction errors compared with previous approaches.
Highlights
In modern computer animation production, motion capture solutions simplify animators’ lives.Motion capture systems quickly capture human motion and its naturalness
Based on the studies of Ayyappa [33], Marks [34], and Loudon et al [35], the presented segmentation process considered the eight phases characterizing a single cycle of the human gait: initial contact (IC), loading response (LR), mid-stance (MST), terminal stance (TST), pre-swing (PSW), initial swing (ISW), mid-swing (MSW), and terminal swing (TSW)
The segmentation process uses contact with the ground information of the foot parts and a crossing event (LCE for left and RCE for right foot) if the ankle is in front of or behind the foot and are abbreviated as follows: right toe contact (RT), right heel contact (RH), left toe contact (LT), left heel contact (LH), right crossing event (RCE), and left crossing event (LCE)
Summary
In modern computer animation production, motion capture solutions simplify animators’ lives. Considering the prohibitive cost of acquiring a high-quality motion capture system and the difficulties associated with reconstructing the locomotion sequences for large numbers of people (e.g., capturing the locomotion sequences of a group of pedestrians to analyze their reactions and interactions in order to compose virtual crowds), affordable solutions that provide such functionality are highly desirable. Based on this aim, this paper presents a method of reconstructing the full-body.
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