Minimal Motion Capture with Inverse Kinematics for Articulated Human Figure Animation
Animating an articulated figure usually requires expensive hardware in terms of motion capture equipment, processing power and rendering power. This implies a high cost system and thus eliminates the use of personal computers to drive avatars in virtual environments. We propose a system to animate an articulated human upper body in real-time, using minimal motion capture trackers to provide position and orientation for the limbs. The system has to drive an avatar in a virtual environment on a low-end computer. The cost of the motion capture equipment must be relatively low (hence the use of minimal trackers). We discuss the various types of motion capture equipment and decide to use electromagnetic trackers which are adequate for our requirements while being reasonably priced. We also discuss the use of inverse kinematics to solve for the articulated chains making up the topology of the articulated figure. Furthermore, we offer a method to describe articulated chains as well as a process to specify the reach of up to four link chains with various levels of redundancy for use in articulated figures. We then provide various types of constraints to reduce the redundancy of non-defined articulated chains, specifically for chains found in an articulated human upper body. Such methods include a way to solve for the redundancy in the orientation of the neck link, as well as three different methods to solve the redundancy of the articulated human arm. The first method involves eliminating a degree of freedom from the chain, thus reducing its redundancy. The second method calculates the elevation angle of the elbow position from the elevation angle of the hand. The third method determines the actual position of the elbow from an average of previous positions of the elbow according to the position and orientation of the hand. The previous positions of the elbow are captured during the calibration process. The redundancy of the neck is easily solved due to the small amount of redundancy in the chain. When solving the arm, the first method which should give a perfect result in theory, gives a poor result in practice due to the limitations of both the motion capture equipment and the design. The second method provides an adequate result for the position of the redundant elbow in most cases although fails in some cases. Still it benefits from a simple approach as well as very little need for calibration. The third method provides the most accurate method of the three for the position of the redundant elbow although it also fails in some cases. This method however requires a long calibration session for each user. The last two methods allow for the calibration data to be used in latter session, thus reducing considerably the calibration required. In combination with a virtual reality system, these processes allow for the real-time animation of an articulated figure to drive avatars in virtual environments or for low quality animation on a low-end computer.
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