| Vis||Graphics||Computer Vision / Image processing|| HPC||Submission deadline|
|SIGGRAPH '14|| ||Jan. 20/Jan. 21, 2014|
|IEEE Vis '14|| ||Mar. 21/Mar. 31, 2014|
| || ||ACM MM '14|| ||Mar. 31/Apr. 14, 2014 |
| || || ||SC '14||Apr. 4/Apr. 11, 2014 |
|PG '14|| ||May 30/May 31, 2014|
SIGGRAPH Asia '13 | |May 14, 2013
PacificVis '14 | |Sep. 02, 2013
I3D '14 | |Oct. 22, 2013
CVPR '14 | |Nov. 01, 2013
EuroVis '14 | |Nov. 29/Dec. 06, 2013
Here lists the interesting papers/tools/research ideas I found recently. As I also post these references to my participating projects, the right sidebar show RSSs to these projects' site for these posts.
I am especially interested techniques that create effective overviews for videos:Techniques for interactive video cubism.
S. S. Fels, E. Lee, and K. Mase.
In MM ’00: Proceedings of ACM Multimedia 2000, pages 368–370, 2000.Video visualization.
G. Daniel and M. Chen.
In VIS ’03: Proceedings of the IEEE Visualization 2003, pages 409–416, 2003.Computational time-lapse video.
Eric P. Bennett and Leonard McMillan.
In SIGGRAPH 2007
, Article 102, 2007.Factored time-lapse video.
Kalyan Sunkavalli, Wojciech Matusik, Hanspeter Pfister, and Szymon Rusinkiewicz.
In SIGGRAPH 2007
, Article 101, 2007.Exploring video streams using slit-tear visualizations.
A. Tang, S. Greenberg, and S. Fels.
In AVI ’08: Proceedings of the Working Conference on Advanced Visual Interfaces 2008, pages 191–198, 2008.Action-based multifield video visualization.
R. P. Botchen, S. Bachthaler, F. Schick, M. Chen, G. Mori, D. Weiskopf, and T. Ertl.
IEEE Transactions on Visualization and Computer Graphics 14(4):885–899, 2008.Dynamic video narratives.
Carlos D. Correa and Kwan-Liu Ma.
In SIGGRAPH '10
88 , 9 pages, 2010.
In computer vision, image processing, and computer graphics, the researchers have tried to optimize the computation of local value distribution since it can be applied to common image filtering such as median filtering and bilateral filtering. Recently, the researchers in the visualization society also study algorithms to efficiently query histograms for arbitrary regions and the applications of local distribution. This document lists papers about efficient computation of local distribution from Cartesian grids from these research areas.
This list will keep updating. So far (2013/11/11) my observation is that different area has different research interests about histogram.
- The papers in computer graphics and image processing are more related to faster filtering for images/videos.
- The papers in information visualization are more related to fast query in order to query the histogram of arbitrary sub block in high dimensional data. (PS. so far I only know 2 papers from info vis researchers in recent years).
- The papers in scientific visualization are more related to the application side of local histograms. My hypothesis is that the researchers are looking for concrete examples how histograms can be applied for scientific visualization problems.
- On the other hand, scientific visualization conferences also have papers about fast histogram query. These papers are mainly from the research group of Prof. Han-Wei Shen.
Ppers in Computer Vision and Graphics avenues
F. Porikli.Integral histogram: a fast way to extract histograms in cartesian spaces.
In CVPR ’05: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
, volume 1, pages 829 – 836, 2005.
Ben Weiss. Fast median and bilateral filtering.
In ACM SIGGRAPH 2006
, pp. 519-526, 2006.
An O(log N) algorithm to quickly update the histogram per pixel. Based on the histograms, median filtering and bilateral filtering can be efficiently computed.
F. Porikli.Constant time O (1) bilateral filtering.
In CVPR ’08: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
, volume 1, pp. 1 – 8, 2008.
This paper shows that with box filters in the spatial domain, the bilateral filter can be computed on the region histogram. As a result, by combining integral histograms, bilateral filtering can be efficiently applied.
Kass, Michael and Justin Solomon.Smoothed Local Histogram Filters.ACM Transactions on Graphics
, 29(4): Article No. 100, 2010.
This paper uses kernel-density estimate other than histogram to estimate the local distribution. This paper shows that the computation of kernels-based estimate for all pixels is equivalent to the convolution of kernel value at all point. As a result, the computation can be done in the frequency domain via FFT, which is independent to the region size.
Markus Hadwiger, Ronell Sicat, Johanna Beyer, Jens Krüger, and Torsten Möller.Sparse PDF maps for non-linear multi-resolution image operations.ACM Transaction on Graphics
, 31(6): Article No. 133, 2012.
This paper present sparse PDF map. Essentially, sparse PDF map stores the models of span distribution.
Papers in Visualization avenue
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
The main focus of this paper is to use information theory to guide the visualization of vector fields. In order to apply information theory, local distribution should be efficiently computed in order to compute information theoretic metrics such as entropy, mutual information, and conditional entropy.
D. Thompson, J. Levine, J. Bennett, P.-T. Bremer, A. Gyulassy, V. Pascucci, and P. Pebay.Analysis of large-scale scalar data using hixels.
In LDAV ’11: Proceedings of the IEEE Symposium on Large Data Analysis and Visualization
, pp. 23 –30, 2011.
Essentially, HIXEL means that each pixel or grid points stores 1 histogram. Based on hixels, this paper show multiple application in scientific visualizaition.
S. Liu, J. Levine, P.-T. Bremer, and V. Pascucci.Gaussian mixture model based volume visualization.
In LDAV ’12: Proceedings of the IEEE Symposium on Large Data Analysis and Visualization
, pp. 73 - 77, 2012.
This paper can be treated as an extension of HIXEL, but the distribution of each pixel is represented by Gaussian mixture models. As storing the parameters of Gaussian kernels is more storage-efficient than storing histograms, this paper presents a GPU-based implementation to utilize the distributions for volume 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, 2012.
This paper studies different strategies to parallelize the computation of region histograms on parallel computers.
Steven Martin and Han-Wei Shen,Transformations for Volumetric Range Distribution Queries.
In PacificVis '13: Proceedings of IEEE Pacific Visualization Symposium
, pp. 89 - 96, 2013.
This paper presents span distributions, which are the distributions of a spatial interval (or called span). With span distributions, the region histogram of arbitrary axis-region can be computed in logarithmic time.
Zhicheng Liu, Biye Jiang, Jeffrey Heer imMens: Real-Time Interactive Visual Exploration of Big DataComputer Graphics Forum
, 32(3): pp. 421-430, 2013.
T.-Y. Lee and H.-W. ShenEfficient Local Statistical Analysis via Integral Histograms with Discrete Wavelet Transform.IEEE Transactions on Visualization and Computer Graphics
, 19(12):2693-2701, Dec., 2013.
As integral histograms provide fast compression, its storage overhead can be large to 3D data. This paper use Wavelet transform to compress the integral histograms to sparse set of coefficients.
Lauro Lins, James T. Klosowski, and Carlos ScheideggerNanocubes for Real-Time Exploration of Spatiotemporal DatasetsIEEE Transactions on Visualization and Computer Graphics
, 19(12):2456 - 2465, 2013.
Appendix: Papers for fast bilateral filtering (without explicit computation of histogram computation)
Sylvain Paris and Frédo Durand. 2009.A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach.International Journal on Computer Vision
, 81(1):24-52, 2009.
This paper presents an interesting idea to converts the non-linear bilateral filtering operator to a linear convolution operator into a homogeneous coordinates in the product of the Cartesian grids and the value range.
YANG, Q., TAN, K. H., AND AHUJA, N.Real-time O(1) bilateral filtering.
In CVPR ’09: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
, pp. 557–564, 2009.
Sylvain Paris, Pierre Kornprobst, Jack Tumblin and Fr ́edo DurandBilateral Filtering: Theory and ApplicationsFoundations and Trends in Computer Graphics and Vision
, 4(1): 1 - 7, 2008.
This is cool. I want to use it to analyze whether certain topics have more self citations than others.
The following paragraph is quoted from the official site http://www.icir.org/christian/scholar.html
Google Scholar is great resource, but it's lacking an
API. Until there is one,
is a Python module that implements a querier and parser for
Google Scholar's output. Its classes can be used
independently, but it can also be invoked as a command-line
tool. It could definitely use a few more features, such as
detailed author extraction and multi-page crawling. If
you're interested in adding features, do send patches!
(Thanks to those of you who have—you know who you are.)
Note:This script only use BeautifulSoup
. Only version 3
can work. Change the line from BeautifulSoup import BeautifulSoup
to from bs4 import BeautifulSoup
does not help.
Here is the result I search. It seems that only the author name can be used to query, but I prefer to search with the paper title. Otherwise, it will be more helpful if it can return the authors too.
$ python scholar.py --author="Teng-Yok Lee" "Visualization"
Title An information-theoretic framework for flow visualization
Citations list http://scholar.google.com/scholar?cites=9106169218819595071&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=9106169218819595071&hl=en&as_sdt=1,5
Title Visualization and exploration of temporal trend relationships in multivariate time-varying data
Citations list http://scholar.google.com/scholar?cites=2642186061934580966&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=2642186061934580966&hl=en&as_sdt=1,5
Title View point evaluation and streamline filtering for flow visualization
Citations list http://scholar.google.com/scholar?cites=441434512775469568&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=441434512775469568&hl=en&as_sdt=1,5
Title Scalable parallel building blocks for custom data analysis
Citations list http://scholar.google.com/scholar?cites=13422225121812586831&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=13422225121812586831&hl=en&as_sdt=1,5
Title A study of parallel particle tracing for steady-state and time-varying flow fields
Citations list http://scholar.google.com/scholar?cites=2563345291252687165&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=2563345291252687165&hl=en&as_sdt=1,5
Title Visualizing time-varying features with tac-based distance fields
Citations list http://scholar.google.com/scholar?cites=6779999163248662192&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=6779999163248662192&hl=en&as_sdt=1,5
Title An image-based modeling approach to gpu-based unstructured grid volume rendering
Citations list http://scholar.google.com/scholar?cites=16150139904233454381&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=16150139904233454381&hl=en&as_sdt=1,5
Title Load-balanced parallel streamline generation on large scale vector fields
Citations list http://scholar.google.com/scholar?cites=15819879486830507892&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=15819879486830507892&hl=en&as_sdt=1,5
Title Cyclestack: Inferring periodic behavior via temporal sequence visualization in ultrasound video
Citations list http://scholar.google.com/scholar?cites=405296597063639844&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=405296597063639844&hl=en&as_sdt=1,5
Title Exploring flow fields using fractal analysis of field lines
Citations list http://scholar.google.com/scholar?cites=15634671221111833227&as_sdt=2005&sciodt=1,5&hl=en
Versions list http://scholar.google.com/scholar?cluster=15634671221111833227&hl=en&as_sdt=1,5
|10/13 - 10/19||Jonathan Ragan-Kelley,
Saman Amarasinghe, and
Decoupling Algorithms from Schedules for Easy Optimization of Image Processing Pipelines
In SIGGRAPH 2012.
|10/20 - 10/26||Johannes Kopf,
Sing Bing Kang |
Quality Prediction for Image Completion
In SIGGRAPH Asia 2012.
|10/27 - 11/02||Eduardo Gastal and
Adaptive Manifolds for Real-Time High-Dimensional Filtering.
In SIGGRAPH 2012.
|11/03 - 11/09||Manuel Lang,
Aljoscha Smolic, and
Practical Temporal Consistency for Image-Based Graphics Applications
In SIGGRAPH 2012.
|11/10 - 11/16||James Tompkin,
Kwang In Kim,
Jan Kautz, and
Videoscapes: Exploring Sparse, Unstructured Video Collections.
In SIGGRAPH 2012.
11/17 - 11/23 Thanksgiving.
|11/24 - 11/30|| Lauro Lins, James T. Klosowski, and Carlos Scheidegger |
Nanocubes for Real-Time Exploration of Spatiotemporal Datasets
In InfoVis 2013.
|12/01 - 12/07||Julius Parulek and Andrea Brambilla|
Fast Blending Scheme for Molecular Surface Representation
In SciVis 2013.
|12/08 - 12/14||Wei-Hsien Hsu, Yubo Zhang, and Kwan-Liu Ma|
A Multi-Criteria Approach to Camera Motion Design for Volume Data Animation
In SciVis 2013.
|12/15 - 12/21|| Samer S. Barakat, Xavier Tricoche|
Adaptive Refinement of the Flow Map Using Sparse Samples
In SciVis 2013.
|12/22 - 12/28 ||Zhong Fan,
Discontinuity-Aware Video Object Cutout.
In SIGGRAPH Asia 2012.
More to read:
S. Paris, P. Kornprobst, J. Tumblin, and F. Durand,
Filtering: Theory and Applications
Foundations and Trends® in Computer
Graphics and Vision, vol. 4, no. 1, pp. 1‐73, Aug. 2009. doi:
Sylvain Paris and Frédo Durand. 2009.
A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach.
Int. J. Comput. Vision 81, 1 (January 2009), 24-52. DOI=10.1007/s11263-007-0110-8 http://dx.doi.org/10.1007/s11263-007-0110-8
Jiawen Chen, Sylvain Paris, and Frédo Durand. 2007.
Real-time edge-aware image processing with the bilateral grid.
ACM Trans. Graph. 26, 3, Article 103 (July 2007). DOI=10.1145/1276377.1276506 http://doi.acm.org/10.1145/1276377.1276506
YANG, Q., TAN, K. H., AND AHUJA, N.
Real-time O(1) bilateral filtering.
In CVPR 2009, pp. 557–564.
The information are copied from SIGGRAPH 2012 Paper
and SIGGRAPH Asia 2012 Papers
(maintained by Ke-Sen Huang
PETS 2006 Benchmark Data
Benchmarks for Advanced Video and Signal based Surveillance
LIVE Video Quality Database from Prof.
Alan C. Bovi
's Laboratory for Image & Video Engineering at The
University of Texas at Austin. .
NICTA Pedestrian Dataset
Thanks for Chih Hsiang Chang Chang in the ECE department of UT Dallas provides these links.
As I just released my GPU-based acceleration for brute force distance computation, now I am curious about those fast algorithms (and curious how to implement them on GPUs).
Breu, H.; Gil, J.; Kirkpatrick, D.; Werman, M.,
Linear time Euclidean distance transform algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.17, no.5, pp.529,533, May 1995
|07/22 - 07/28||Markus
Hadwiger, Ronell Sicat, Johanna Beyer, Jens Krüger, and Torsten Möller.
Sparse PDF maps for non-linear multi-resolution image
ACM Trans. Graph. 31, 6, Article 133 (November 2012), 12 pages.
|07/29 - 08/04 ||Sylvain Paris, Samuel W. Hasinoff, and Jan Kautz|
Local Laplacian Filters: Edge-aware Image Processing with a Laplacian Pyramid
ACM Transactions on Graphics (Proceedings of SIGGRAPH 2011)
|08/05 - 08/11||Kass, Michael and Justin Solomon. |
Local Histogram Filters.
|08/12 - 08/18 ||Zicheng Liao,
Hugues Hoppe |
Automated Video Looping with Progressive Dynamism
|08/19 - 08/25 ||Neal Wadhwa, Michael Rubinstein, Fredo Durand, William T. Freeman|
Phase-based Video Motion Processing
The complete numbers can be seen on http://eagereyes.org/acceptance-rates
. Here I mainly listed the years I participated:
IEEE Vis (SciVis):
|Acceptance rates (%)
| 2013||126 ||31 ||25 |
||Acceptance rates (%)
| 2013||151||38 ||25 |
The submissions of IEEE Vis were especially high (more than 150) between 2000 and 2012. Between 2005 and 2009, the numbers of submission were even higher than 200 (except 2008)! Nevertheless, now the number of submission to Vis is dropping in the recent two years (2012 and 2013).
InfoVis was growing till 2011. On 2011, infovis even had more submissions than vis. Then InfoVis starts to lose submissions as well. I am curious how to explain it.
I cannot find the links in VGTC's official site via the page of SciVis '13, but I found them on the page
of LDAV '13
still has both links.
Copy right form: http://www.cs.sfu.ca/~vis/Tasks/copyright.html
Release form: http://www.cs.sfu.ca/~vis/Tasks/releaseForm.html