Determining control values of an animation model using performance capture
US-9600742-B2 · Mar 21, 2017 · US
US10055874B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10055874-B2 |
| Application number | US-201514831021-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 20, 2015 |
| Priority date | Aug 20, 2015 |
| Publication date | Aug 21, 2018 |
| Grant date | Aug 21, 2018 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
In some embodiments a method of transferring facial expressions from a subject to a computer-generated character is provided where the method includes receiving positional information from a motion capture session of the subject representing a performance having facial expressions to be transferred to the computer-generated character, receiving a first animation model that represents the subject, and receiving a second animation model that represents the computer-generated character. Each of the first and second animation models can include a plurality of adjustable controls that define geometries of the model and that can be adjusted to present different facial expressions on the model, and where the first and second animation models are designed so that setting the same values for the same set of adjustable controls in each model generates a similar facial poses on the models. The method further includes determining a solution, including values for at least some of the plurality of controls, that matches the first animation model to the positional information to reproduce the facial expressions from the performance to the first animation model, retargeting the facial expressions from the performance to the second animation model using the solution; and thereafter, synchronizing lip movement of the second animation model with lip movement from the first animation model.
Opening claim text (preview).
What is claimed is: 1. A method of transferring facial expressions from a subject to a computer-generated character, the method comprising: receiving positional information from a motion capture session of the subject representing a performance having facial expressions to be transferred to the computer-generated character; receiving a first animation model that represents the subject and a second animation model that represents the computer-generated character, each of the first and second animation models including a plurality of adjustable controls that define geometries of the model and that can be adjusted to present different facial expressions on the model, wherein setting the same values for corresponding sets of adjustable controls in the models generates a similar facial poses on the models; determining a solution that matches the first animation model to the positional information to reproduce the facial expressions from the performance to the first animation model, the solution including values for at least some of the plurality of adjustable controls; retargeting the facial expressions from the performance to the second animation model using the solution; and thereafter, synchronizing lip movement of the second animation model with lip movement from the first animation model. 2. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 1 wherein synchronizing lip movement of the second animation model with lip movement from the first animation model comprises: determining a visible percentage of teeth for the first animation model; determining a visible percentage of teeth for the second animation model; and determining if the visible percentage of teeth for the second animation model matches the visible percentage of teeth for the first animation model, and if not, adjusting the visible percentage of teeth in the second animation model to more closely match the percentage in the first animation model. 3. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 2 wherein adjusting the visible percentage of teeth in the second animation model to more closely match the percentage in the first animation model includes moving either or both upper and lower lip shapes of the second animation model. 4. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 3 wherein a match between the visible percentage of teeth for the second animation model and the visible percentage of teeth for the first animation model occurs when the percentages are within a predetermined amount of each other. 5. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 3 wherein the lip shapes are moved according to a binary search algorithm, and wherein the method further comprises repeating a sequence of: (i) determining a visible percentage of teeth for the second animation model, and (ii) determining if the visible percentage of teeth for the second animation model matches the visible percentage of teeth for the first animation model, and if not, adjusting the visible percentage of teeth in the second animation model to more closely match the percentage in the first animation model until the visible percentages match. 6. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 3 wherein: determining a visible percentage of teeth for the first animation model includes: (i) determining an occluding contour of both the upper or lower lips of the first animation model, (ii) determining a distance between a root and a tip for each of the upper and lower teeth of the first animation model, (iii) computing an intersection between the occluding contour and the tooth lines of the upper and lower teeth of the first animation model, and (iv) calculating a percentage of visible upper teeth and a percentage of visible lower teeth for the first animation model; and determining a visible percentage of teeth for the second animation model includes: (i) determining an occluding contour of both the upper or lower lips of the second animation model, (ii) determining a distance between a root and a tip for each of the upper and lower teeth of the second animation model, (iii) computing an intersection between the occluding contour and the tooth lines of the upper and lower teeth of the second animation model, and (iv) calculating a percentage of visible upper teeth and a percentage of visible lower teeth for the second animation model. 7. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 1 wherein synchronizing lip movement of the creature with lip movement from the first animation model comprises: determining a jaw opening of the first animation model; determining a jaw opening for the second animation model; and determining if the jaw opening of the second animation model matches the jaw opening of the first animation model, and if not, adjusting the jaw opening of the second animation model to more closely match the jaw opening of the first animation model. 8. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 7 wherein determining if the jaw opening of the second animation model matches the jaw opening of the first animation model is performed only if the jaw opening of the second animation model is less than a predetermined amount. 9. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 7 wherein determining a jaw opening for each of the actor and second animation models includes: determining a distance between roots of upper and lower teeth of the respective rig; determining a distance between tips of upper and lower teeth of the respective rig; and computing a ratio of the distance between the roots of the upper and lower teeth and the distance between the tips of the upper and lower teeth. 10. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 7 wherein adjusting the jaw opening of the second animation model to more closely match the jaw opening of the first animation model includes raising or lowering the lower jaw. 11. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 7 wherein the jaw opening is adjusted according to a binary search algorithm and wherein the method further comprises repeating a sequence of: (i) determining a jaw opening of the second animation model, and (ii) determining if the jaw opening of the second animation model matches the jaw opening of the first animation model, and if not, adjusting the jaw opening of the second animation model to more closely match the jaw opening of the first animation model until the jaw openings match. 12. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 7 wherein a match between the jaw opening of the second animation model and the jaw opening of the first animation model occurs when the openings are within a predetermined amount of each other. 13. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 1 wherein synchronizing lip movement of the creature with lip movement from the first animation model comprises: determining a jaw opening of the first animation model, determining a jaw opening for the s
Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components · CPC title
of characters, e.g. humans, animals or virtual beings · CPC title
using feature-based methods, e.g. the tracking of corners or segments · CPC title
Marker · CPC title
Facial expression recognition · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.