Interactive Full-Body Motion Capture Using Infrared Sensor Network

Abstract

Traditional motion capture (mocap) has been well-studied in visual science for the last decades. However the field is mostly about capturing precise animation to be used in specific applications after intensive post processing such as studying biomechanics or rigging models in movies. These data sets are normally captured in complex laboratory environments with sophisticated equipment thus making motion capture a field that is mostly exclusive to professional animators. In addition, obtrusive sensors must be attached to actors and calibrated within the capturing system, resulting in limited and unnatural motion. In recent year the rise of computer vision and interactive entertainment opened the gate for a different type of motion capture which focuses on producing optical markerless or mechanical sensorless motion capture. Furthermore a wide array of low-cost device are released that are easy to use for less mission critical applications. This paper describes a new technique of using multiple infrared devices to process data from multiple infrared sensors to enhance the flexibility and accuracy of the markerless mocap using commodity devices such as Kinect. The method involves analyzing each individual sensor data, decompose and rebuild them into a uniformed skeleton across all sensors. We then assign criteria to define the confidence level of captured signal from sensor. Each sensor operates on its own process and communicates through MPI. Our method emphasizes on the need of minimum calculation overhead for better real time performance while being able to maintain good scalability.