Automated inspection system
US-2024420305-A1 · Dec 19, 2024 · US
US9400921B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9400921-B2 |
| Application number | US-85239801-A |
| Country | US |
| Kind code | B2 |
| Filing date | May 9, 2001 |
| Priority date | May 9, 2001 |
| Publication date | Jul 26, 2016 |
| Grant date | Jul 26, 2016 |
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A method and system using a data-driven model for monocular face tracking are disclosed, which provide a versatile system for tracking three-dimensional (3D) images, e.g., a face, using a single camera. For one method, stereo data based on input image sequences is obtained. A 3D model is built using the obtained stereo data. A monocular image sequence is tracked using the built 3D model. Principal Component Analysis (PCA) can be applied to the stereo data to learn, e.g., possible facial deformations, and to build a data-driven 3D model (“3D face model”). The 3D face model can be used to approximate a generic shape (e.g., facial pose) as a linear combination of shape basis vectors based on the PCA analysis.
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What is claimed is: 1. A method for image processing comprising: obtaining stereo data based on input image sequences from of varying facial expressions: building a three-dimensional (3D) model using the obtained stereo data to obtain principal shape vectors; and tracking a second input image sequence using the 3D model to approximate a linear combination of the principal shape vectors of a facial expression in the second input image sequence, wherein the second input image sequence is a monocular image sequence. 2. The method of claim 1 , wherein the building of the 3D model includes processing the obtained stereo data using a Principal Component Analysis (PCA). 3. The method of claim 2 , wherein the processed stereo data using PCA allows the 3D model to approximate a generic shape as the linear combination of the shape basis vectors. 4. The method of claim 1 , wherein the tracking of the monocular image sequence includes tracking of a monocular image sequence of facial deformations using the built 3D model. 5. A computing system comprising: an input unit to stereo data based on input image sequences from of varying facial expressions; and a processing unit to build a three-dimensional (3D) model using the obtained stereo data to approximate a generic shape as a linear combination of shape basis vectors and track a second input image sequence using the 3D model to approximate a linear combination of the principal shape vectors of a facial expression in the second input image sequence, wherein the second input image sequence is a monocular image sequence. 6. The computing system of claim 5 , wherein the processing unit is to process the obtained stereo data using a Principal Component Analysis (PCA). 7. The computing system of claim 6 , wherein the processed stereo data using PCA allows the 3D model to approximate a generic shape as the linear combination of the shape basis vectors. 8. The computing system of claim 5 , wherein the processing unit is to track a monocular image sequence of facial deformations using the built 3D model. 9. A non-transitory machine-readable medium providing instructions, which if executed by a processor, causes the processor to perform an operation comprising: obtaining stereo data based on input image sequences from of varying facial expressions: building a three-dimensional (3D) model using the obtained stereo data to approximate a generic shape as a linear combination of shape basis vectors; and tracking a second input image sequence using the 3D model to approximate a linear combination of the principal shape vectors of a facial expression in the second input image sequence, wherein the second input image sequence is a monocular image sequence. 10. The machine-readable medium of claim 9 , further providing instructions, which if executed by the processor, causes the processor to perform an operation comprising: processing the obtained stereo data using a Principal Component Analysis (PCA). 11. The machine-readable medium of claim 10 , further providing instructions, which if executed by the processor, causes the processor to perform an operation comprising: approximate a generic shape as the linear combination of the shape basis vectors based on the processed stereo data using PCA. 12. The machine-readable medium of claim 9 , further providing instructions, which if executed by the processor, causes the processor to perform an operation comprising: tracking of a monocular image sequence of facial deformations using the built 3D model.
Video; Image sequence · CPC title
involving models · CPC title
Three-dimensional [3D] modelling for computer graphics · CPC title
Depth or disparity estimation from stereoscopic image signals · CPC title
Recording image signals; Reproducing recorded image signals · CPC title
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