History of Motion Capture for Computer Character Animation

History of Motion Capture for Computer Character Animation

The use of motion capture for computer character animation is relatively new, having begun in the late 1970's, and only now beginning to become widespread. Motion capture is the recording of human body movement (or other movement) for immediate or delayed analysis and playback. Motion capture for computer character animation involves the mapping of human motion onto the motion of a computer character. To get convincing motion for the human characters, Disney studios traced animation over film footage of live actors playing out the scenes. This method, called rotoscoping, has been successfully used for human characters ever since.The rotoscoping was invented by max fleischer in 1915.The first cartoon character has to be rotoscope was "koko the clown".He want to use koko to convinced the big studio in the new process for the project.Walt Disney use the rotoscoping technique in 1937 to create motion of human characteristic in snow white.The decision of using rotoscoping technique is realistic human motion. In 1970's it began to be feasible to animate characters by computer, animators adapted traditional techniques,includingrotoscoping.There is several name in the motion capture history;

Pioneers of Motion Capture
Eadweard Muybridge (1830 - 1904) - pioneer photographer of the moving image
Étienne-Jules Marey - First person to analyze human and animal motion with video
Harold E. "Doc" Edgerton (1903-1990) -High Speed stroboscopic photography
Max Fleischer (1915) - Rotoscoping
Lee Harrison III (1960's) - Scanimation
Walt Disney - Multiplane Camera

The motion capture problems
The goal of motion capture is to record the movement of a performer (typically,but not always,human) in a compact and usable manner.Computer graphics and computer vision usually abstract the body into a small number of rigid segments that rotate relative to one another.The motion capture problem we consider therefore must have the following form: given a single stream of video observations of a performer, compute a 3D skeletal representation of the motion of sufficient quality to be useful for animation.
The specific challenges of animation make the problem even tougher.

- Unlike applications such as recognition and surveillance, animation does care about small details.

- Jitter and wobbles often come from uncertainty in computations,

- The importance of high frequencies means that filtering is not a viable tool for noise removal at video sampling rates.

- The unpredictability and unusual motions that we need to capture limit the strength of the models we can apply.