Human Motion Capture Driven by Orientation Measurements

Motion-capture techniques are rarely based on orientation measurements for two main reasons: (1) optical motion-capture systems are designed for tracking object position rather than their orientation (which can be deduced from several trackers), (2) known animation techniques, like inverse kinematics or geometric algorithms, require position targets constantly, but orientation inputs only occasionally. We propose a complete human motion-capture technique based essentially on orientation measurements. The position measurement is used only for recovering the global position of the performer. This method allows fast tracking of human gestures for interactive applications as well as high rate recording. Several motion-capture optimizations, including the multijoint technique, improve the posture realism. This work is well suited for magnetic-based systems that rely more on orientation registration (in our environment) than position measurements that necessitate difficult system calibration. 1 Introduction With the rapid progress of virtual reality (VR) technology, the real-time motion control of synthetic actors has become a major research direction in character animation. Performance animation is assuming an increasingly important role in multimedia applications and entertainment. In the near future, we expect that any human individual can be modeled and placed in a virtual environment , and the synthetic creatures inhabiting the virtual world will communicate with real persons through a wide spectrum of behaviors. Magnetic-based motion capture faces several limitations, though some are common to other motion-capture measurement techniques (e.g., optical systems) as well. The possible sources of mismatch between the virtual model and the performer postures are calibration error, slipping of sensors relative to bones, electronic noise, and revolute joints of simplified model. In this paper, we present a motion-capture technique called real-time Anatomical Converter, designed for converting magnetic sensor data in anatomical angles. The converter uses a novel method, the multijoint control, allowing several joints to be driven using only one sensor. As the position measurements of a magnetic sensor often lack linearity, we propose a method that does not rely on such imprecise measurements from several sensors. Instead, we recover the global position of the performer using one sensor fastened to the waist while his/her body posture is computed from orientation measurements that are returned by all the sensors.