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Liang Wang
lwangd@cs.uky.edu
GRAphics and VIsion TechnologY Lab
(GRAVITY Lab) Center for Visualization
and Virtual Environments Department of
Computer Science, University of Kentucky Advisor: Dr. Ruigang Yang |
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Short Bio
Liang Wang is a Ph.D.
candidate in the Computer Science Department at University of Kentucky. His
research interests include a variety of topics in computer vision, computer
graphics, and image processing, especially on stereo matching, structure from
motion, 3D reconstruction, image-based modeling and rendering, bi-layer
segmentation and matting for live video, and multi-projector display system.
Before starting his Ph.D. study, Liang Wang received his Bachelor’s degree in Computer Science and Engineering
from Beihang University, Beijing, China in 2004. In summer 2007 and 2008, Liang
was a research intern at Adobe's Advanced Technology Labs, respectively. More information can be
found in this CV and Google scholar citations.
Journal Articles
Automatic Real-Time Video Matting Using Time-of-Flight Camera and Multichannel Poisson Equations
Liang Wang, Minglun Gong, Chenxi Zhang, Ruigang Yang, Cha Zhang, and Yee-Hong Yang
International Journal of Computer Vision (IJCV), accepted May 2011, DOI: 10.1007/s11263-011-0471-x (online first)
Reliability Fusion of Time-of-Flight Depth and Stereo Geometry for High Quality Depth Maps
Jiejie Zhu, Liang Wang, Ruigang Yang, James Davis, and Zhigeng Pan
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 33, No. 7, Page 1400-1414, May 2011
Spatial-Temporal
Fusion for High Accuracy Depth Maps using Dynamic MRFs (pdf)
Jiejie Zhu, Liang
Wang, Jizhou Gao, and Ruigang
Yang
IEEE Transactions on Pattern Analysis and Machine
Intelligence (TPAMI), Vol. 32, No. 5, Page 899-909, May 2010
Stereo
Matching with Color-weighted Correlation, Hierarchical Belief Propagation and
Occlusion Handling (pdf)
IEEE Transactions on Pattern Analysis and Machine
Intelligence (TPAMI), Vol. 31, No. 3, Page 492-504, March 2009
Detailed
Real-Time Urban 3D Reconstruction From Video (pdf)
M. Pollefeys, D. Nister, J.-M. Frahm, A. Akbarzadeh, P. Mordohai,
B. Clipp, C. Engels, D. Gallup, S.-J. Kim, P. Merrell, C. Salmi, S. Sinha, B.
Talton, L. Wang, Q. Yang, H. Stewenius, R. Yang, G.
Welch, and H. Towles
International Journal of Computer Vision (IJCV), Vol. 78, Issue 2,
Pages 143 - 167, July 2008
BRDF Invariant Stereo using Light Transport Constancy (pdf)
Liang Wang,
IEEE Transactions on Pattern Analysis and Machine Intelligence
(TPAMI), Vol. 29, No. 9, Page 1616-1626, September 2007
A
Performance Study on Different Cost Aggregation Approaches used in Real-time
Stereo Matching (pdf)
Minglun Gong,
Ruigang Yang, Liang Wang, and Mingwei Gong
International Journal of Computer Vision (IJCV), Vol. 75, No. 2,
Page 283-296, November 2007
* Note: IEEE-TPAMI and IJCV
are considered to be the top two computer vision journals and both have very
high impact factors that ranked among top 3 in subject category Comp. sc., artificial intelligence.
Selected Conference & Workshop Publications
Global
Stereo Matching Leveraged by Sparse Ground Control Points (pdf)
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2011
Semantic Segmentation of Urban
Scenes Using Dense Depth Maps (pdf)
European Conference on Computer Vision (ECCV), 2010
[supplementary
material – 12.3 MB]
A
Constant-Space Belief Propagation Algorithm for Stereo Matching (pdf)
IEEE Computer Society Conference on Computer Vision and
Pattern Recognition (CVPR), 2010
TofCut:
Towards Robust Real-Time Foreground Extraction Using a Time-of-Flight Camera (pdf)
Fifth International Symposium on 3D Data Processing, Visualization
and Transmission (3DPVT), 2010 (Oral)
[supplementary
material – 11MB], [binary segmentation datasets]
Search
Space Reduction for MRF Stereo (pdf)
European
Conference on Computer Vision (ECCV), 2008
Stereoscopic
Inpainting: Joint Color and Depth Completion from Stereo Images (pdf)
IEEE Computer Society Conference on Computer Vision and
Pattern Recognition (CVPR), 2008
Fusion
of Time-of-Flight Depth and Stereo for High Accuracy Depth Maps (pdf)
IEEE Computer Society Conference on Computer Vision and
Pattern Recognition (CVPR), 2008 (Oral)
Multi-Projector Display with Continuous Self-Calibration (pdf)
Jin Zhou, Liang Wang,
Amir Akbarzadeh, and Ruigang Yang
Fifth ACM/IEEE International Workshop on
Projector-Camera Systems (PROCAMS), in conjunction with SIGGRAPH 2008 (Best Paper Award)
[supplementary material – 4 MB]
Real-Time
Visibility-Based Fusion of Depth Maps (pdf)
P. Merrell, A.
Akbarzadeh, L. Wang, P. Mordohai, J-M. Frahm,
R. Yang, D. Nister, and M. Pollefeys
IEEE International Conference on Computer
Vision (ICCV), 2007 (Oral)
Light Fall-off Stereo (pdf)
Miao Liao, Liang Wang,
Ruigang Yang, and Minglun Gong
IEEE Computer Society Conference on Computer Vision and
Pattern Recognition (CVPR), 2007
High-Quality
Real-Time Stereo using Adaptive Cost Aggregation and Dynamic Programming (pdf)
Liang Wang, Miao Liao, Minglun Gong, Ruigang Yang, and David Nister
Third International Symposium on 3D Data Processing,
Visualization and Transmission (3DPVT), 2006 (Oral)
How Far Can We Go with
Local Optimization in Real-Time Stereo Matching (pdf)
Liang Wang,
Mingwei Gong, Minglun Gong, and Ruigang Yang
Third International Symposium on 3D Data Processing, Visualization
and Transmission (3DPVT), 2006
Towards
Urban 3D Reconstruction from Video (pdf)
A. Akbarzadeh, J.-M. Frahm, P. Mordohai, B. Clipp, C. Engels, D.
Gallup, P. Merrell, M. Phelps, S. Sinha, B. Talton, L. Wang, Q. Yang, H. Stewenius, R. Yang, G. Welch, H. Towles, D. Nister,
and M. Pollefeys
Third International Symposium on 3D Data Processing, Visualization
and Transmission (3DPVT), 2006 (Invited Paper)
Real-Time
Global Stereo Matching Using Hierarchical Belief Propagation (pdf)
Qingxiong Yang, Liang
Wang, Ruigang Yang, Shengnan
Wang, Miao Liao, and David Nister
The British Machine Vision Conference (BMVC), 2006
Stereo
Matching with Color-Weighted Correlation, Hierarchical Belief Propagation and
Occlusion Handling (pdf)
Qingxiong Yang, Liang
Wang, Ruigang Yang, Henrik
Stewenius, and David Nister
IEEE Computer
Society Conference on Computer Vision and Pattern Recognition (CVPR), 2006
BRDF Invariant Stereo using Light Transport Constancy (pdf)
James Davis,
Ruigang Yang, and Liang Wang
IEEE International Conference on Computer Vision (ICCV), 2005
(Oral)
* Note: ICCV, CVPR, and ECCV
are considered to be the top 3 computer vision conferences and are highly
competitive with low acceptance rate <30%.
Selected Research Projects
Multi-projector
display with continuous self-calibration
Most existing calibration techniques for
multi-projector display system require that the display configuration remain
fixed during the display process. We present a new approach to continuously
re-calibrate the projection system to automatically adapt to the display
configuration changes, while the multi-projector system is being used without
interruption. By rigidly attaching a camera to each projector, we argument the
projector with sensing capability and use the camera to provide online
close-loop control. In contrast to previous auto or continuous projector
calibration solutions, our approach can be used on surfaces of arbitrary
geometry and can handle both projector and display surface movement, yielding more
flexible system configuration and better scalability. related paper PROCAMS08, video clips planar (2.27MB), corner (1.66MB), curved (3MB)
Search
space reduction for MRF stereo
We present an algorithm to reduce per-pixel
search ranges for Markov Random Fields-based stereo algorithms. Our algorithm
is based on the intuitions that reliably matched pixels need less regularization
in the energy minimization and neighboring pixels should have similar disparity
search ranges if their pixel values are similar. We propose a novel bi-labeling
process to classify reliable and unreliable pixels that incorporate left-right
consistency checks. We then propagate the reliable disparities into unreliable
regions to form a complete disparity map and construct per-pixel search ranges
based on the difference between the disparity map after propagation and the one
computed from a winner-take-all method. Experimental results evaluated on the
Middlebury stereo benchmark show our proposed algorithm is able to achieve 77%
average reduction rate while preserving satisfactory accuracy. related paper ECCV08
Stereoscopic
inpainting
We present a novel
algorithm for simultaneous color and depth inpainting. The algorithm takes
stereo images and estimated disparity maps as input and fills in missing color
and depth information introduced by occlusions or object removal. We first
complete the disparities for the occlusion regions using a segmentation-based
approach. The completed disparities can be used to facilitate the user in
labeling objects to be removed. Since part of the removed regions in one image
is visible in the other, we mutually complete the two images through 3D
warping. Finally, we complete the remaining unknown regions using a
depth-assisted texture synthesis technique, which simultaneously fills in both
color and depth. We demonstrate the effectiveness of the proposed algorithm on
several challenging data sets. related paper CVPR08
Light
fall-off stereo
We present light fall-off stereo–LFS–a new
method for computing depth from scenes beyond Lambertian reflectance and
texture. LFS takes a number of images from a stationary camera as the
illumination source moves away from the scene. Based on the inverse square law
for light intensity, the ratio images are directly related to scene depth from
the perspective of the light source. Using this as the invariant, we developed
both local and global methods for depth recovery. Compared to previous
reconstruction methods for non-lamebrain scenes, LFS needs as few as two
images, does not require calibrated camera or light sources, or reference
objects in the scene. related papers CVPR07, ICIP08
3D
urban reconstruction
The goal of this project
is to build a data collection system and a processing pipeline for automatic
geo-registered 3D reconstruction of urban scenes from video. The system
collects multiple video streams, as well as GPS and INS measurements in order
to place the reconstructed models in geo-registered coordinates. Besides high
quality in terms of both geometry and appearance, we aim at real-time
performance. Even though our processing pipeline is currently far from being
real-time, we select techniques and we design processing modules that can
achieve fast performance on multiple CPUs and GPUs aiming at real-time
performance in the near future. (find more) related papers 3DPVT06, 3D-ARCH07, ICCV07, IJCV08
High quality and real-time stereo algorithms
I have been working on designing
algorithms for dense two-frame stereo matching problem aiming at both high
reconstruction quality and real-time performance. Evaluation using the
benchmark Middlebury stereo database shows that our
algorithms are among the best in terms of both quality and speed. The real-time
performance mainly comes from the parallelism of today’s commodity graphics
hardware. related papers 3DPVT06-oral, 3DPVT06, BMVC06, CVPR06, IJCV07, TPAMI08
BRDF invariant stereo using light transport constancy
Nearly all existing methods for stereo
reconstruction assume that scene reflectance is Lambertian and make use of
brightness constancy as a matching invariant. We introduce a new invariant for
stereo reconstruction called Light Transport Constancy, which allows completely
arbitrary scene reflectance (BRDFs). This invariant can be used to formulate a
rank constraint on multi-view stereo matching when the scene is observed by
several lighting configurations, in which only the lighting intensity varies.
In addition, we show that this multi-view constraint can be used with as few as
two cameras and two lighting configurations. This new constraint can be used to
provide BRDF invariance to any existing stereo method, whenever appropriate
lighting variation is available.
Contact
Email: lwangd AT cs DOT uky DOT edu
Phone: 859-257-1257 EXT 82332
Mail: Center for Visualization and
Virtual Environments
University of Kentucky
1 Quality Street, Suite 800
Lexington, KY 40507-1464, USA