Scientists at Carnegie Mellon University along with the researchers at Disney Research Pittsburg are developing what is being called the next generation of motion capture animation technique. Current motion capture techniques use reference markers on the body of an actor and then infra red cameras mounted in a room to capture the movement of the actor.
This technique (PDF Link to paper) is limited to indoor filming as the sun interferes with the system outdoors. Yaser Sheikh an assistant research professor with the Carnegie Mellon University’s Robotics Institute said that this system was confined to close space. However the new motion capture system can be used outside and over long stretches of space.
The wearable camera system makes it possible to reconstruct the relative and global motions of an actor thanks to a process called structure from motion (SfM). Takeo Kanade, a CMU professor of computer science and robotics and a pioneer in computer vision, developed SfM 20 years ago as a means of determining the three-dimensional structure of an object by analyzing the images from a camera as it moves around the object, or as the object moves past the camera.
In this application, SfM is not used primarily to analyze objects in a person's surroundings, but to estimate the pose of the cameras on the person. Researchers used Velcro to mount 20 lightweight cameras on the limbs, and trunk of each subject. Each camera was calibrated with respect to a reference structure. Each person then performed a range-of-motion exercise that allowed the system to automatically build a digital skeleton and estimate positions of cameras with respect to that skeleton.
SfM is used to estimate rough position and orientation of limbs as the actor moves through an environment and to collect sparse 3D information about the environment that can provide context for the captured motion. The rough position and orientation of limbs serves as an initial guess for a refinement step that optimizes the configuration of the body and its location in the environment, resulting in the final motion capture result.
The quality of motion capture from body-mounted cameras does not yet match the fidelity of traditional motion capture, Shiratori said, but will improve as the resolution of small video cameras continues to improve.
The technique requires a significant amount of computational power; a minute of motion capture now can require an entire day to process. Future work will include efforts to find computational shortcuts, such as performing many of the steps simultaneously through parallel processing.