final project presentation schedulecse.sc.edu/~tongy/csce867/lect/lect23.pdf · 2019-04-15 ·...
TRANSCRIPT
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Final Project Presentation Schedule
April 22 April 24 April 29
Fengyao & Yuan Xiaoyi Yudong & Anjia
Jun Jared Bokai
Liang Halee Gaofeng &
Jiandong
Wesley Xiangyu Long
Denise
A single presentation is required for a team
Each presentation has 12 + 3 minutes Q&A
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Materials covered in the presentation
For a hands-on project
• An introduction of the background
• A brief literature review
• Methodology of your proposed method
• Experimental results if any
For a survey project
• An introduction of the background
• A discussion on the papers you reviewed
• Comparison of the methods/groups you reviewed
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Final Project Requirement
Written report due time: 11:59:00pm, Friday, May 3
Report format: the same as a complete conference paper
Academic integrity (avoiding plagiarism)
• don’t copy other person’s work
• describe using your own words
• complete citation and acknowledgement whenever you use any other work (either published or online)
Evaluation
• Abstract (be clear and concise) 20%
• written report (be clear, complete, correct, etc.,) 50%
• oral presentation 30%
• quality: publication-level project – extra credits up to 10%
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Active Appearance Model
Model
• For every triangle, an affine transformation is employed to
established the correspondence between the model and the image
• A set of local affine transformation approximates nonrigid
transformation Piecewise affine transformation
Adapted from Matthews and Baker, “Active Appearance Models Revisited”, IJCV 2004
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AAM Model Instantiation
Matthews and Baker, “Active Appearance Models Revisited”, IJCV 2004
Piecewise affine warping
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Registration – AAM Fitting
Goal: obtain optimal shape and appearance parameters to minimize the appearance difference between the model and the target image
• Difference is measured in the same coordinate system – the mean shape
• Assume an initial parameter set is known, iteratively update the parameters
min𝜆,𝐩
𝐀𝟎 𝐱 +
𝑖=1
𝐾
𝜆𝑖 𝐀𝐢 𝐱 − I 𝐖(𝐱; 𝐩)
2
Reconstructed appearance Warped image
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Registration – AAM Fitting
• Find optimal p by minimizing the first term
• Fixed p, solve 𝝀 by minimizing the second term
𝐀𝟎 𝐱 +
𝑖=1
𝐾
𝜆𝑖 𝐀𝐢 𝐱 − I 𝐖(𝐱; 𝐩)
2
= 𝐀𝟎 𝐱 − I 𝐖(𝐱; 𝐩) 2𝑠𝑝𝑎𝑛(𝐀𝐢)
⊥ + 𝐀𝟎 𝐱 +
𝑖=1
𝐾
𝜆𝑖 𝐀𝐢 𝐱 − I 𝐖(𝐱; 𝐩)
2
𝑠𝑝𝑎𝑛(𝐀𝐢)
Only depends on p depends on 𝝀
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Registration – AAM Fitting
Forwards compositional image alignment
• Warp the image to the model
Inverse compositional image alignment
• Warp the model to the image
𝛜 = 𝐀𝟎 𝐱 − 𝐈(𝐖(𝐖 𝐱; 𝚫𝐩 ; 𝐩)) 𝟐
𝐖 𝐱;𝐩 ⇐ 𝐖 𝐱; 𝐩 ∘ 𝐖 𝐱; 𝚫𝐩
𝛜 = 𝐀𝟎 𝐖 𝐱;𝚫𝐩 − 𝐈(𝐖(𝐱; 𝐩))𝟐
𝐖 𝐱;𝐩 ⇐ 𝐖 𝐱; 𝐩 ∘ 𝐖 𝐱; 𝚫𝐩 −𝟏
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AAM Fitting
Matthews and Baker, “Active Appearance Models Revisited”, IJCV 2004
https://www.youtube.com/watch?v
=7joASSATdHA
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D.A. Forsyth accompanying Forsyth and Ponce "Computer Vision - A Modern Approach"
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D.A. Forsyth accompanying Forsyth and Ponce "Computer Vision - A Modern Approach"
Register a face with expression to a neutral face
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Reading Assignments
[1] T. F. Cootes. Statistical models of appearance for computer vision. Online technical report available from http://www.face-rec.org/algorithms/AAM/app_models.pdf , Sept. 2001.
[2] T. F. Cootes, G. J. Edwards, and C. J. Taylor. Active appearance models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(6):681–685, June 2001.
[3] I. Matthews and S. Baker, Active Appearance Models Revisited, IJCV 2004.