Research

This page lists my represented publication and projects. The complete publication list can be seen in my CV, DBLP, or Google Scholar. Besides, several useful links are provided too.

My publication mainly covers the following topics 1) Scientific visualization, including volume rendering, flow visualization, and time-varying data visualization, 2) GPGPU and high performance computation for graphics/visualization, and 3) computer vision and machine learning.

Referred Publications

2017

  

Computer vision
Machine learning

T.-Y. Lee, S. Patil, S. Ramalingam, Y. Taguchi, and B. BEnes
Barcode: Global Binary Patterns for Fast Visual Inference.
In 3DV '17: International Conference on 3D Vision, 2017
(acceptance rate: 73/146 = 50%).


Computer vision
Machine learning

C. Feng, M.-Y. Liu, C.-C. Kao, and T.-Y. Lee
Deep Active Learning for Civil Infrastructure Defect Detection and Classification.
In IWCCE '17: International Workshop on Computing for Civil Engineering, 2017.
pdf

2014

  


Flow visualization
A Chaudhuri, T.-Y. Lee, H.-W. Shen, and R. Wenger
Exploring Flow Fields Using Space-filling Analysis of Streamlines
IEEE Transactions on Visualization and Computer Graphics, 20(10): 1392 - 1404, Oct., 2014.
preprint, ieeexplorer


Flow visualization
Volume rendering
A Chaudhuri, T.-H. Wei, T.-Y. Lee, H.-W. Shen, and T. Peterka.
Efficient Range Distribution Query for Visualizing Scientific Data.
In PacificVis ‘14: Proceedings of the IEEE Pacific Visualization Symposium, pp. 201 - 208, Yokohama, Japan, 2014
(acceptance rate: 29/99 = 29%).
preprint

2013


 
Computer graphicsT.-Y. Lee and H.-W. Shen,
Efficient Local Statistical Analysis via Integral Histograms with Discrete Wavelet Transform
IEEE Transactions on Visualization and Computer Graphics, 19(12):2693-2701, Dec., 2013
(Special Issue for IEEE SciVis '13, acceptance rate: 31/126 = 24%).
code, preprint, errata, slides, video

Time-varying data visualization
Visual analytics
T.-Y. Lee, X. Tong, H.-W. Shen, P. C. Wong, S. Hagos, and L. Leung,
Feature Tracking and Visualization of Madden-Julian Oscillation in Climate Simulation.
IEEE Computer Graphics and Applications (Theme Issue on Big Data Visualization), 33(4): 29-37, 2013.
demo, doi, video
Volume rendering
T.-H. Wei, T.-Y. Lee, and H.-W. Shen,
Evaluating Isosurfaces with Level-set-based Information Maps.
Computer Graphics Forum, 30(3):1-10, 2013
(Special Issue for EuroVis 2013, acceptance rate: 49/177 = 28%).
code, preprint, slides

  Flow visualization
K. Lu, A. Chaudhuri, T.-Y. Lee, H.-W. Shen, and P. C. Wong,
Exploring Vector Fields with Distribution-based Streamline Analysis.
In PacificVis '13: Proceedings of the IEEE Pacific Visualization Symposium, pp.257 - 264, Sydney, Australia, 2013
(Acceptance rate: 34/118 = 29%).
preprint

2012

   
  Flow visualization
Parallel graphics & visualization

 
B. Nouanesengsy, T.-Y. Lee, K. Lu, H.-W. Shen, and T. Peterka,
Parallel Particle Advection and FTLE Computation for Time-Varying Flow Fields.
In SC ‘12: ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis. Salt Lake City, UT, Nov., 2012.
(Acceptance rate: 100/472 = 21%)
pdf

  Flow visualization
Parallel graphics & visualization

C.-M. Chen, B. Nouanesengsy, T.-Y. Lee, and H.-W. Shen,

Flow-guided File Layout for Out-of-core Pathline Computation.

In LDAV ‘12: IEEE Symposium on Large-Scale Data Analysis and Visualization, pp. 109 - 112, Seattle, WA, Oct., 2012
(Acceptance rate: 18/34 = 53%. Nominated for Best Paper.)
pdf



Time-varying data visualization

X. Tong, T.-Y. Lee, and H.-W. Shen,

Salient Time Steps Selection from Large Scale Time-Varying Data Sets with Dynamic Time Warping.

In LDAV ‘12: IEEE Symposium on Large-Scale Data Analysis and Visualization, pp. 49 - 56, Seattle, WA, Oct., 2012
(Acceptance rate: 18/34 = 53%).
pdf

  Parallel graphics & visualization

A. Chaudhuri, T.-Y. Lee, B. Zhou, C. Wang, T. Xu, H.-W. Shen, T. Peterka and Y.-J. Chiang,

Scalable Computation of Distributions from Large Scale Data Sets.

In LDAV ‘12: IEEE Symposium on Large-Scale Data Analysis and Visualization, pp. 113 - 120, Seattle, WA, Oct., 2012
(Acceptance rate: 18/34 = 53%).
pdf

Flow visualization
Parallel graphics & visualization
C.-M. Chen, L. Xu, T.-Y. Lee, and  H.-W. Shen,
Flow-Guided File Layout for Out-Of-Core Streamline Computation.
In  PacificVis '12: Proceedings of the IEEE Pacific Visualization Symposium, pp. 145 - 152, Songdo, Korea, March, 2012.
(Acceptance rate: 30/89 = 33.7%).
pdf

2011

   
Flow visualization
Parallel graphics & visualization
B. Nouanesengsy, T.-Y. Lee, and H.-W. Shen,
Load-Balanced Parallel Streamline Generation on Large Scale Vector Fields
.
IEEE Transactions on Visualization and Computer Graphics, 17(12):1785-1794, 2011
(Special Issue for IEEE Visualization 2011, acceptance rate: 49/194 = 25%).
pdf

  Flow visualization

T.-Y. Lee, O. Mishchenko, H.-W. Shen, and R. Crawfis,
View Point Evaluation and Streamline Filtering for Flow Visualization.
In PacificVis '11: Proceedings of the IEEE Pacific Visualization Symposium, pp. 83 - 90, Hong Kong, March, 2011
(Acceptance rate: 27/81 = 33%).
pdf, slides, video 1, video 2, video 3 

2010

   






Flow visualization
 
L. Xu, T.-Y. Lee, and H.-W. Shen,
An Information-Theoretic Framework for Flow Visualization.
IEEE Transactions on Visualization and Computer Graphics
, 16(6):1216-1224, Nov.-Dec., 2010
(Special Issue for IEEE Visualization 2010, acceptance rate: 45/185 = 26%).
code, pdf, slides


 
Time-varying data visualization

T.-Y. Lee, A. Chaudhuri, F. Porikli, and H.-W. Shen,
CycleStack: Inferring Periodic Behavior via Temporal Sequence Visualization in Ultrasound Video
.
In PacificVis '10: Proceedings of the IEEE Pacific Visualization Symposium, pp. 89-96, Taipei, Taiwan, March, 2010 
(Acceptance rate: 27/84 = 32%).
pdf, slides, video

2009

   
 
Time-varying data visualization

T.-Y. Lee, and H.-W. Shen,
Visualization and Exploration of Temporal Trend Relationships in Multivariate Time-Varying Data
.
IEEE Transactions on Visualization and Computer Graphics
, 15(6):1359–1366, 2009
(Special Issue for IEEE Visualization 2009, acceptance rate: 54/202 = 27%).
pdf, slides


 
GPGPU
Time-varying data visualization

T.-Y. Lee, and H.-W. Shen,
Visualizing Time-Varying Features with TAC-based Distance Fields.
In PacificVis '09: Proceedings of the IEEE Pacific Visualization Symposium, pp. 1-8, Beijin, China, April, 2009
(Acceptance rate: 26/66 = 40%).
pdf, slides

2006

   

GPGPU
Volume rendering
N. Shareef, T.-Y. Lee, H.-W. Shen, and K. Mueller,
An Image-based Modelling Approach to GPU-based Rendering of Unstructured Grids.
In VG '06: Proceedings of the Eurographics/IEEE VGTC Workshop on Volume Graphics 2006, pp. 31-38, Boston, MA, July, 2006
(Acceptance rate: 13/38 = 34%).
pdf

Additional Publications

Journals/Conferences

  1. W. Abbeloos, S. Caccamo, E. Ataer-Cansizoglu, Y. Taguchi, C. Feng, and T.-Y. Lee, Detecting and Grouping Identical Objects for Region Proposal and Classification. In CVPR '17 Workshop on Deep Learning for Robotic Vision, 2017 (arXiv).
  2. C. Hori, T. Hori, T.-Y. Lee, K. Sumi, J. R. Hershey, and T. K. Marks, Attention-Based Multimodal Fusion for Video Description, 2017 (arXiv).
  3. P. C. Wong, H.-W. Shen, R. Leung, S. Hagos, T.-Y. Lee, X. Tong, and K. Lu, Visual Analytics of Large-Scale Climate Model Data. In LDAV '14: Proceedings of the IEEE Symposium on Large Data Analysis and Visualization 2014, Paris, Frances, November 2014.
  4. T. Peterka, R. Ross, W. Kendall, A. Gyulassy, V. Pascucci, H.-W. Shen, T.-Y. Lee, and A. Chaudhuri, Scalable Parallel Building Blocks for Custom Data Analysis. In LDAV '11: Proceedings of the IEEE Symposium on Large Data Analysis and Visualization 2011, pp. 105-112, Providence, Rhode Island, October 2011 (Acceptance rate: 25/37=66%, pdf, slides).
  5. H.-W. Shen, T.-Y. Lee, A. Chaudhuri, and B. Nouanesengsey, Visual Analytics for Enabling Extreme Scale Scientific Discovery. In SciDAC 2011, Denver, Colorado, July, 2011 (pdf).
  6. T. Peterka, R. Ross, B. Nouanesengsey, T.-Y. Lee, H.-W. Shen, W. Kendall, and J. Huang, A Study of Parallel Particle Tracing for Steady-State and Time-Varying Flow Fields. In IPDPS '11: Proceedings of the IEEE International Parallel & Distributed Processing Symposium 2011, pp. 580-591, Anchorage, Alaska, May, 2011. (Acceptance rate: 112/571 = 20%, pdf).

Technical Reports/Patents

  1. A. Chaudhuri, T.-Y. Lee, H.-W. Shen, M. Khoury and R. Wenger. Exploring Flow Fields Using Fractal Analysis of Field Lines. OSU-CISRC-4/11-TR15.
  2. F. Porikli, and T.-Y. Lee, Method for estimating pattern of change of patient. Japan Patent Application JP2010240400A, October, 2010.
  3. F. Porikli, and T.-Y. Lee, Enhanced Visualizations for Ultrasound Videos. United States Patent Application 20100246914 and 20110007952, September, 2010.
  4. T.-Y. Lee and H.-W. Shen, Visualizing Time-Varying Features with TAC-based Distance Fields. OSU-CISRC-10/08-TR53 (pdf).

Presentations/Posters

  1. A. Chaudhuri, T.-Y. Lee, H.-W. Shen, and T. Peterka, Efficient Range Distribution Query in Large-scale Scientific Data. In LDAV '13: IEEE Symposium on Large Data Analysis and Visualization 2013 Poster Session, Atlanta, Georgia, October 2013 (Best Poster).
  2. A. Chaudhuri, T.-Y. Lee, H.-W. Shen, M. khoury and R. Wenger. Exploring Flow Fields Using Fractal Analysis of Field Lines. In VisWeek '12: IEEE Visualization, Seattle, WA, Oct 2012 (Best Poster).
  3. K. Lu, A. Chaudhuri, T.-Y. Lee, A. G. Suttmiller, H.-W. Shen, and P. C. Wong, Exploring Vector Fields with Distribution-based Streamline Analysis. In VisWeek '12: IEEE Visualization, Seattle, WA, 2012.
  4. X. Liu, T.-Y. Lee, and H.-W. Shen, Interactive Word Cloud Rendering with Semantic Zooming. In VisWeek '12: IEEE Information Visualization, Seattle, WA, 2012.
  5. Exploring Large Scale Scientific Data  Using Information Theory (Authors: A. Chaudhuri, T.-Y. Lee, H.-W. Shen, T. Peterka, C. Wang, T. Xu, B. Zhou, and Y.-J. Chiang). In CoDA '12: Conference on Data Analysis 2012, Santa Fe, New Mexico, Feb., 2012.

  6. C.-M. Chen, L. Xu, T.-Y. Lee, and H.-W. Shen, A Flow Guided File Layout for Out-Of-Core Streamline Computation. In LDAV '11: IEEE Symposium on Large Data Analysis and Visualization 2011 Poster Session, Providence, Rhode Island, October 2011.
  7. Information Theory for Visualization and Data Analysis. In CScADS Summer 2011 Workshop 2: Scientific Data and Analytics for Extreme Scale Computing, Tahoe, CA, Jul., 2011 (slides).
  8. Visualizing Time-Varying Features with TAC-based Distance Fields. In Grad Research Poster Exhibit, Department of Computer Science & Engineering, The Ohio State University, Apr., 2009.
  9. Visualizing Time-Varying Features with TAC-based Distance Fields. In Demonstrations at Ohio State University in IEEE VisWeek 2008, Columbus, OH, Oct. 22, 2008.
  10. Y. Tu, and T.-Y. Lee, Visual Discovery of Box Office and Oscars in Movie Data. In IEEE InfoVis 2007 Contest (pdf).

Subpages (1): Past Projects in OSU
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Teng-Yok Lee,
Sep 12, 2011, 1:20 PM
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Teng-Yok Lee,
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