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Facial motion capture
Facial motion capture is the process of electronically converting the movements of a person's face into a digital database using cameras or laser scanners. This database may then be used to produce computer graphics (CG), computer animation for movies, games, or real-time avatars. Because the motion of CGI characters is derived from the movements of real people, it results in a more realistic and nuanced computer character animation than if the animation were created manually.
A facial motion capture database describes the coordinates or relative positions of reference points on the actor's face. The capture may be in two dimensions, in which case the capture process is sometimes called "expression tracking", or in three dimensions. Two-dimensional capture can be achieved using a single camera and capture software. This produces less sophisticated tracking, and is unable to fully capture three-dimensional motions such as head rotation. Three-dimensional capture is accomplished using multi-camera rigs or laser marker system. Such systems are typically far more expensive, complicated, and time-consuming to use. Two predominant technologies exist: marker and markerless tracking systems.
Facial motion capture is related to body motion capture, but is more challenging due to the higher resolution requirements to detect and track subtle expressions possible from small movements of the eyes and lips. These movements are often less than a few millimeters, requiring even greater resolution and fidelity and different filtering techniques than usually used in full body capture. The additional constraints of the face also allow more opportunities for using models and rules.
Facial expression capture is similar to facial motion capture. It is a process of using visual or mechanical means to manipulate computer-generated characters with input from human faces, or to recognize emotions from a user.
One of the first papers discussing performance-driven animation was published by Lance Williams in 1990. There, he describes 'a means of acquiring the expressions of realfaces, and applying them to computer-generated faces'.
Traditional marker-based systems apply up to 350 markers to the actors face and track the marker movement with high resolution cameras. This has been used on movies such as The Polar Express and Beowulf to allow an actor such as Tom Hanks to drive the facial expressions of several different characters. Unfortunately, this is relatively cumbersome and makes the actors expressions overly driven once the smoothing and filtering have taken place. Next generation systems such as CaptiveMotion utilize offshoots of the traditional marker-based system with higher levels of details.
Active LED Marker technology is currently being used to drive facial animation in real-time to provide user feedback.
Markerless technologies use the features of the face such as nostrils, the corners of the lips and eyes, and wrinkles and then track them. This technology is discussed and demonstrated at CMU, IBM, University of Manchester (where much of this started with Tim Cootes, Gareth Edwards and Chris Taylor) and other locations, using active appearance models, principal component analysis, eigen tracking, deformable surface models and other techniques to track the desired facial features from frame to frame. This technology is much less cumbersome, and allows greater expression for the actor.
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Facial motion capture AI simulator
(@Facial motion capture_simulator)
Facial motion capture
Facial motion capture is the process of electronically converting the movements of a person's face into a digital database using cameras or laser scanners. This database may then be used to produce computer graphics (CG), computer animation for movies, games, or real-time avatars. Because the motion of CGI characters is derived from the movements of real people, it results in a more realistic and nuanced computer character animation than if the animation were created manually.
A facial motion capture database describes the coordinates or relative positions of reference points on the actor's face. The capture may be in two dimensions, in which case the capture process is sometimes called "expression tracking", or in three dimensions. Two-dimensional capture can be achieved using a single camera and capture software. This produces less sophisticated tracking, and is unable to fully capture three-dimensional motions such as head rotation. Three-dimensional capture is accomplished using multi-camera rigs or laser marker system. Such systems are typically far more expensive, complicated, and time-consuming to use. Two predominant technologies exist: marker and markerless tracking systems.
Facial motion capture is related to body motion capture, but is more challenging due to the higher resolution requirements to detect and track subtle expressions possible from small movements of the eyes and lips. These movements are often less than a few millimeters, requiring even greater resolution and fidelity and different filtering techniques than usually used in full body capture. The additional constraints of the face also allow more opportunities for using models and rules.
Facial expression capture is similar to facial motion capture. It is a process of using visual or mechanical means to manipulate computer-generated characters with input from human faces, or to recognize emotions from a user.
One of the first papers discussing performance-driven animation was published by Lance Williams in 1990. There, he describes 'a means of acquiring the expressions of realfaces, and applying them to computer-generated faces'.
Traditional marker-based systems apply up to 350 markers to the actors face and track the marker movement with high resolution cameras. This has been used on movies such as The Polar Express and Beowulf to allow an actor such as Tom Hanks to drive the facial expressions of several different characters. Unfortunately, this is relatively cumbersome and makes the actors expressions overly driven once the smoothing and filtering have taken place. Next generation systems such as CaptiveMotion utilize offshoots of the traditional marker-based system with higher levels of details.
Active LED Marker technology is currently being used to drive facial animation in real-time to provide user feedback.
Markerless technologies use the features of the face such as nostrils, the corners of the lips and eyes, and wrinkles and then track them. This technology is discussed and demonstrated at CMU, IBM, University of Manchester (where much of this started with Tim Cootes, Gareth Edwards and Chris Taylor) and other locations, using active appearance models, principal component analysis, eigen tracking, deformable surface models and other techniques to track the desired facial features from frame to frame. This technology is much less cumbersome, and allows greater expression for the actor.