Facial motion capture

Facial motion capture, or facial MoCap, is a subset of the motion capture field, frequently used for machine vision systems. A user?s face is viewed, usually full on, and relative head motion filtered out. The individual motion of the cheeks, lips, chin, eyes and eyebrows are studied, and used for facial expression recognition.

See Also: MoCap, Performance Capture, High Fidelity Facial Motion Capture, Marker-based Facial motion capture, Markerless Facial motion capture

Below, we offer a selection of links from our resource databases which may match this term.

Facial MoCap Facial motion capture

High Fidelity Facial Motion Capture Marker-based Facial motion capture

Markerless Facial motion capture Performance Capture

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Video games need 'realism boost'
BBC article about how to add authenticity to VR, goes beyond graphics, also encompassing extensive use of motion capture to catalogue how stance, gait and the tiny movements of facial muscles combine when people display different emotions.

Horses and Other Animals in Motion: 45 Classic Photographic Sequences

Horses and other Animals in Motion is a collection of, as the title says, 45 sets of photographs of horses hauling, walking, trotting, etc., plus sequences of donkeys, an ox, pig, dog, cat, deer and other animals capture details of anatomy and movement. These images, were taken by the definitive expert in the field, Eadweard Muybridge.

Stop Staring: Facial Modeling and Animation Done Right

An expressive face is a work of art. Constantly moving and changing. Lips, brows, frown lines, each is in constant motion. Stop Staring analyses facial structures and movements, then shows animators how to bring life to the faces of their characters.

MoCap for Movement Analysis
Promising work by QuinteQ on real-time motion capture without excessive hardware, holds promise for MoCap use in public VR.

Combining MoCap and Gesture Recognition
MoCap - Motion Capture - for all its impressive abilities, has definite limitations in terms of sensory fidelity, the expense and bulk of the rig. Gesture control is cheap and captures every little movement, but easily overwhelmed. Is a hybrid system possible?

Cheapening the Cost of Motion Sensors
Motion sensors are starting to creep into a whole plethora of applications. They are the linch pins of haptics, of 3D pointers, of stress based sensor networks and locomotive VR interfaces. Yet, there's a problem. Small, discrete motion sensors, tiny enough to be built into larger devices the size say, of a Wii-remote or a 6 ounce HMD, are extremely difficult and expensive to produce.

Only A Few Basic Emotional Expressions are the Root of All Others
We have known for some time that different cultures perceive different facial expressions as conveying different emotional states, and likewise in different cultures different facial expressions are made. Rather than having ream after ream of options for facial expression sequence files, might there be a far better way to handle such regional differences in recognising avatar-based visual emotional states?

EFIT-V: The Evolved Police Sketch Artist
The problem with photofit and sketch artists is, that human memory is not geared to remember fine facial features, even of people they know well. How then, to take advantage of facial recognition when looking for a suspect's identity?

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