Research On Realtime Human Motion Animation Control

Interactive control of human characters would allow the intuitive control of characters in computer/video games, the control of avatars for virtual reality, electronically mediated communication or teleconferencing, and the rapid prototyping of character animations for movies. To be useful, such a system must be capable of controlling a lifelike character interactively, precisely, and intuitively. Building an animation system for home use is particularly challenging because the system should also be low-cost and not require a considerable amount of time, skill, or artistry.This thesis explores an approach that exploits a wide range of spatial-temporal constraints for interactive animation control. The control inputs from such a system are often low-dimensional, contain far less information than actual human motion, and thus cannot be directly used for precise control of high-dimensional characters. However, natural human motion is highly constrained; the movements of the degrees of freedom of the limbs or facial expressions are not independent. Our hypothesis is that the knowledge about natural human motion embedded in a domain-specific motion capture database can be used to transform the under constrained user input into realistic human motions. The spatial-temporal coherence embedded in the motion data allows us to control high-dimensional human animations with low-dimensional user input.We analysis three different statistical models for human motion, and demonstrate the power and flexibility of this approach through three different models:(1) using local linear regression method and several inertial sensors to control a complex3D human motion in real time;(2) using window-based local model and sparse control signals to control a complex3D full-body human motion;(3) using mixture of factor analyzer and a few of inertial sensors to real time control a full-body human movement. For all three statistical models, we assess the quality of the results by comparisons with those created by a commercial optical motion capture system. We demonstrate the quality of the animation created by all three systems is comparable to commercial motion capture systems but requires less expense, time, and space to suit up the user.