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Graphics, Vision, HCI. K.P. Chan Wenping Wang Li-Yi Wei Kenneth Wong Yizhou Yu. Li-Yi Wei. Background Stanford (95-01), NVIDIA (01-05), MSR (05-11) Research Nominal: Graphics, HCI, parallelism Actual: Computing natural repetitions (Computer science is about repetitions) - PowerPoint PPT Presentation
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Graphics, Vision, HCIGraphics, Vision, HCI
K.P. Chan
Wenping Wang
Li-Yi Wei
Kenneth Wong
Yizhou Yu
Li-Yi WeiLi-Yi Wei
Background
Stanford (95-01), NVIDIA (01-05), MSR (05-11)
Research
Nominal: Graphics, HCI, parallelism
Actual: Computing natural repetitions
(Computer science is about repetitions)
Can work on almost anything + have fun
I tailor projects for individual students (so they also have fun)
Computing natural repetitionsComputing natural repetitions
interactauto
procedural(parametric)
data driven(non-parametric)
parallelrandom
parallelism HCIgraphics
ParallelPoisson
texture synthesisinverse
synthesis
blue noise
motiontexture HDR
edit
elementtexture
revisioncontrol
differentialanalysis
Discrete element textures[Ma et al. SIGGRAPH 2011]Discrete element textures[Ma et al. SIGGRAPH 2011]
exemplar
domain output
synthesis
SIGGRAPHSIGGRAPH
The coolest (& ass kicking) venue in graphics
Each paper can be worth a PhD thesis
(Just in case you don’t know)
HKU has 4 papers in SIGGRAPH 2012 So we are awesome (in addition to have fun)
input
output
input
output
input
output
Yizhou YuYizhou Yu
Background
Berkeley (PhD 2000), UIUC (2000 - 2010)
Research
Graphics, vision, image processing
• Computational Photography
• Computer Animation
• Geometry Processing
• Medical Imaging
• Video Analytics
Deformation transfer for real time cloth animation [SIGGRAPH 2010]Deformation transfer for real time cloth animation [SIGGRAPH 2010]
DeformationTransformer
Motivation• Real-Time Cloth Animation
– Video games, virtual fashion, etc. • The Problem
– Real-time performance on high-resolution models – PDE Integration, Collision resolution.
Final Fantasy XIII Nurien
Overview• Hybrid Approach :
– Simulate low-res cloth on the GPU– Rely on a data-driven model to transform the
low-res simulation into a high-res animation
DeformationTransformer
An Example
High-Res Dress: 27K Triangles, Low-Res Dress: 200 Triangles Frame Rate: 261
Data-Driven Image Color Theme Enhancement [SIGGRAPH Asia 2010]
Photo Reuse: how to edit a photograph to enhance a desired color impression by exploiting prior knowledge extracted from an existing photo collection?
source image nostalgic lively
Waiting for the right season and illumination could be extremely time-consuming!
Our Goal
Image Color Theme Enhancement
Input Image
desolate
lively
Results
Input Images
happy sad
spring in the air peaceful
Wenping WangWenping Wang
Background
Alberta (PhD 1992), Department Head
Research
Computer graphics
Geometry Processing
Computational geometry
Architectural Design
Scientific Visualization
SIGGRAPH 2006
SIGGRAPH 2007
SIGGRAPH 2008
SIGGRAPH 2008
Kwan-Yee Kenneth WongKwan-Yee Kenneth Wong
Background
Cambridge (PhD 2001)
Research
3D modeling
Video surveillance
Image processing
Pattern recognition
…
3D Model ReconstructionRobust recovery of shapes with unknown
topology from the dual space (PAMI 2007)
contour generator
silhouette N
3D Model ReconstructionRobust recovery of shapes with unknown
topology from the dual space (PAMI 2007)
original surface
dual surface
tangent
operation
tangent
operation
original surface
3D Model ReconstructionRobust recovery of shapes with unknown
topology from the dual space (PAMI 2007)
Eye Gaze TrackingReconstruction of display and eyes from a
single image (CVPR 2010)
27
Eye Gaze TrackingReconstruction of display and eyes from a
single image (CVPR 2010)
28
Kwok-Ping ChanKwok-Ping Chan
Background
HKU (PhD 1989)
Research
• To apply various Machine Learning methods on Pattern Recognitions, such as facial expression recognition.
• Study on Cross Domain Learning where the training and the testing domain are not the same.
Facial Expression RecognitionFacial Expression Recognition
Goal: to recognize one of the seven basic facial expressions:
MethodsMethods
• Dynamic Bayesian Network
• Discriminative Hidden Markov Models
• Discriminative Temporal Topic Models
• Given an image sequence of facial expression, we compute the probability of each expression using the above techniques.
Examples: Smile with blinking eyes:Examples: Smile with blinking eyes:
From input, produce output
similar to input
arbitrary size
Key Publication: CVPR 2009