@article {19647,
	title = {A computational statistics approach for estimating the spatial range of morphogen gradients},
	journal = {Development},
	volume = {138},
	year = {2011},
	month = {2011/11/15/},
	pages = {4867 - 4874},
	abstract = {A crucial issue in studies of morphogen gradients relates to their range: the distance over which they can act as direct regulators of cell signaling, gene expression and cell differentiation. To address this, we present a straightforward statistical framework that can be used in multiple developmental systems. We illustrate the developed approach by providing a point estimate and confidence interval for the spatial range of the graded distribution of nuclear Dorsal, a transcription factor that controls the dorsoventral pattern of the Drosophila embryo.},
	keywords = {Computational Biology, Confidence interval, Dorsal gradient, Drosophila embryo, Morphogen gradient, Statistics},
	isbn = {0950-1991, 1477-9129},
	url = {http://dev.biologists.org/content/138/22/4867},
	author = {Kanodia, Jitendra S. and Kim, Yoosik and Tomer, Raju and Zia Khan and Chung, Kwanghun and Storey, John D. and Lu, Hang and Keller, Philipp J. and Shvartsman, Stanislav Y.}
}
@conference {19042,
	title = {Privacy settings from contextual attributes: A case study using Google Buzz},
	year = {2011},
	month = {2011},
	pages = {257 - 262},
	abstract = {Social networks provide users with privacy settings to control what information is shared with connections and other users. In this paper, we analyze factors influencing changes in privacy-related settings in the Google Buzz social network. Specifically, we show statistics on contextual data related to privacy settings that are derived from crawled datasets and analyze the characteristics of users who changed their privacy settings. We also investigate potential neighboring effects among such users.},
	keywords = {contextual attributes, data privacy, Google Buzz, privacy settings, social networking (online), social networks, Statistics},
	author = {Mashima, D. and Elaine Shi and Chow, R. and Sarkar, P. and Li,C. and Song,D.}
}
@article {12476,
	title = {Online Empirical Evaluation of Tracking Algorithms},
	journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume = {32},
	year = {2010},
	month = {2010/08//},
	pages = {1443 - 1458},
	abstract = {Evaluation of tracking algorithms in the absence of ground truth is a challenging problem. There exist a variety of approaches for this problem, ranging from formal model validation techniques to heuristics that look for mismatches between track properties and the observed data. However, few of these methods scale up to the task of visual tracking, where the models are usually nonlinear and complex and typically lie in a high-dimensional space. Further, scenarios that cause track failures and/or poor tracking performance are also quite diverse for the visual tracking problem. In this paper, we propose an online performance evaluation strategy for tracking systems based on particle filters using a time-reversed Markov chain. The key intuition of our proposed methodology relies on the time-reversible nature of physical motion exhibited by most objects, which in turn should be possessed by a good tracker. In the presence of tracking failures due to occlusion, low SNR, or modeling errors, this reversible nature of the tracker is violated. We use this property for detection of track failures. To evaluate the performance of the tracker at time instant t, we use the posterior of the tracking algorithm to initialize a time-reversed Markov chain. We compute the posterior density of track parameters at the starting time t = 0 by filtering back in time to the initial time instant. The distance between the posterior density of the time-reversed chain (at t = 0) and the prior density used to initialize the tracking algorithm forms the decision statistic for evaluation. It is observed that when the data are generated by the underlying models, the decision statistic takes a low value. We provide a thorough experimental analysis of the evaluation methodology. Specifically, we demonstrate the effectiveness of our approach for tackling common challenges such as occlusion, pose, and illumination changes and provide the Receiver Operating Characteristic (ROC) curves. Finally, we also s how the applicability of the core ideas of the paper to other tracking algorithms such as the Kanade-Lucas-Tomasi (KLT) feature tracker and the mean-shift tracker.},
	keywords = {Back, Biomedical imaging, Computer vision, Filtering, formal model validation techniques, formal verification, ground truth, Kanade Lucas Tomasi feature tracker, Karhunen-Loeve transforms, lighting, Markov processes, mean shift tracker, model validation., online empirical evaluation, particle filtering (numerical methods), Particle filters, Particle tracking, performance evaluation, receiver operating characteristic curves, Robustness, SNR, Statistics, Surveillance, time reversed Markov chain, tracking, tracking algorithms, visual tracking},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2009.135},
	author = {Wu,Hao and Sankaranarayanan,A. C and Chellapa, Rama}
}
@conference {14208,
	title = {Combining powerful local and global statistics for texture description},
	booktitle = {IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009},
	year = {2009},
	month = {2009/06/20/25},
	pages = {573 - 580},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A texture descriptor is proposed, which combines local highly discriminative features with the global statistics of fractal geometry to achieve high descriptive power, but also invariance to geometric and illumination transformations. As local measurements SIFT features are estimated densely at multiple window sizes and discretized. On each of the discretized measurements the fractal dimension is computed to obtain the so-called multifractal spectrum, which is invariant to geometric transformations and illumination changes. Finally to achieve robustness to scale changes, a multi-scale representation of the multifractal spectrum is developed using a framelet system, that is, a redundant tight wavelet frame system. Experiments on classification demonstrate that the descriptor outperforms existing methods on the UIUC as well as the UMD high-resolution dataset.},
	keywords = {Computer science, discretized measurements, fractal geometry, Fractals, geometric transformations, global statistics, Histograms, illumination transformations, image classification, image resolution, Image texture, lighting, local measurements SIFT features, local statistics, MATHEMATICS, multifractal spectrum, multiscale representation, Power engineering and energy, Power engineering computing, Robustness, Solids, Statistics, texture description, UMD high-resolution dataset, wavelet frame system, Wavelet transforms},
	isbn = {978-1-4244-3992-8},
	doi = {10.1109/CVPR.2009.5206741},
	author = {Yong Xu and Si-Bin Huang and Hui Ji and Ferm{\"u}ller, Cornelia}
}
@article {17238,
	title = {Integrating Statistics and Visualization for Exploratory Power: From Long-Term Case Studies to Design Guidelines},
	journal = {IEEE Computer Graphics and Applications},
	volume = {29},
	year = {2009},
	month = {2009/06//May},
	pages = {39 - 51},
	abstract = {Evaluating visual-analytics systems is challenging because laboratory-based controlled experiments might not effectively represent analytical tasks. One such system, Social Action, integrates statistics and visualization in an interactive exploratory tool for social network analysis. This article describes results from long-term case studies with domain experts and extends established design goals for information visualization.},
	keywords = {case studies, Control systems, Data analysis, data mining, data visualisation, Data visualization, data-mining, design guidelines, Employment, exploration, Filters, Guidelines, Information Visualization, insights, laboratory-based controlled experiments, Performance analysis, social network analysis, Social network services, social networking (online), social networks, SocialAction, statistical analysis, Statistics, visual analytics, visual-analytics systems, Visualization},
	isbn = {0272-1716},
	doi = {10.1109/MCG.2009.44},
	author = {Perer,A. and Shneiderman, Ben}
}
@conference {17239,
	title = {Integrating statistics and visualization: case studies of gaining clarity during exploratory data analysis},
	booktitle = {Proceedings of the twenty-sixth annual SIGCHI conference on Human factors in computing systems},
	series = {CHI {\textquoteright}08},
	year = {2008},
	month = {2008///},
	pages = {265 - 274},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Although both statistical methods and visualizations have been used by network analysts, exploratory data analysis remains a challenge. We propose that a tight integration of these technologies in an interactive exploratory tool could dramatically speed insight development. To test the power of this integrated approach, we created a novel social network analysis tool, SocialAction, and conducted four long-term case studies with domain experts, each working on unique data sets with unique problems. The structured replicated case studies show that the integrated approach in SocialAction led to significant discoveries by a political analyst, a bibliometrician, a healthcare consultant, and a counter-terrorism researcher. Our contributions demonstrate that the tight integration of statistics and visualizations improves exploratory data analysis, and that our evaluation methodology for long-term case studies captures the research strategies of data analysts.},
	keywords = {case studies, Evaluation, exploratory data analysis, Information Visualization, social networks, Statistics},
	isbn = {978-1-60558-011-1},
	doi = {10.1145/1357054.1357101},
	url = {http://doi.acm.org/10.1145/1357054.1357101},
	author = {Perer,Adam and Shneiderman, Ben}
}
@inbook {12640,
	title = {Computer Vision, Statistics in},
	booktitle = {Encyclopedia of Statistical SciencesEncyclopedia of Statistical Sciences},
	year = {2006},
	month = {2006///},
	publisher = {John Wiley \& Sons, Inc.},
	organization = {John Wiley \& Sons, Inc.},
	abstract = {Computer Vision (CV) broadly refers to the discipline where extraction of useful 2D and/or 3D information from one or more images is of interest. Useful information could consist of features such as edges, lines, curves and textures, or information about depth, motion, object descriptions, etc. CV problems are usually ill-posed inverse problems. Since the image data is usually obtained from sensors such as video cameras, infrared, radar, etc., the information extraction processes often have to deal with data that is corrupted by noise from the sensors and the environment. Statistics can help in obtaining robust and accurate solutions to these inverse problems by modeling the noise processes. We present here a broad overview of the applications of statistics to different computer vision problems and explain in detail two particular applications, tracking and motion analysis, where statistical approaches have been used very successfully.},
	keywords = {Computer vision, sampling, Statistics, structure from motion, tracking},
	isbn = {9780471667193},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/0471667196.ess3129/abstract},
	author = {Chellapa, Rama and Chowdhury,Amit K. Roy}
}
@article {15400,
	title = {Random doping-induced fluctuations of subthreshold characteristics in MOSFET devices},
	journal = {Solid-State Electronics},
	volume = {47},
	year = {2003},
	month = {2003/11//},
	pages = {2055 - 2061},
	abstract = {The random doping-induced fluctuations of subthreshold characteristics in MOSFET devices are analyzed. A technique for the computations of sensitivity coefficients and variances of subthreshold parameters is presented and applied to the computation of fluctuations of subthreshold current and gate-voltage swing. This technique is based on the linearization of transport equations with respect to the fluctuating quantities. It is computationally much more efficient than purely {\textquotedblleft}statistical{\textquotedblright} methods (Monte-Carlo methods) that are based on the simulations of a large number of devices with different doping realizations. The numerical implementation of this technique is discussed and numerous computational results are presented.},
	keywords = {Fluctuations, Mismatch, MOSFET, Sensitivity analysis, Statistics, Submicron devices},
	isbn = {0038-1101},
	doi = {10.1016/S0038-1101(03)00236-3},
	url = {http://www.sciencedirect.com/science/article/pii/S0038110103002363},
	author = {Andrei,Petru and Mayergoyz, Issak D}
}
@conference {17156,
	title = {Extending understanding of federal statistics in tables},
	booktitle = {Proceedings of the 2000 annual national conference on Digital government research},
	series = {dg.o {\textquoteright}00},
	year = {2000},
	month = {2000///},
	pages = {1 - 7},
	publisher = {Digital Government Society of North America},
	organization = {Digital Government Society of North America},
	abstract = {This paper describes progress toward improving user interfaces for US Federal government statistics that are presented in tables. Based on studies of user behaviors and needs related to statistical tables, we describe interfaces to assist diverse users with a range of statistical literacy to explore, find, understand, and use US Federal government statistics.},
	keywords = {data exploration, dynamic queries, Statistics, tablular data, User interfaces},
	url = {http://dl.acm.org/citation.cfm?id=1123075.1123079},
	author = {Marchionini,Gary and Hert,Carol and Liddy,Liz and Shneiderman, Ben}
}
@article {14166,
	title = {The Ouchi illusion as an artifact of biased flow estimation},
	journal = {Vision Research},
	volume = {40},
	year = {2000},
	month = {2000/01//},
	pages = {77 - 95},
	abstract = {A pattern by Ouchi has the surprising property that small motions can cause illusory relative motion between the inset and background regions. The effect can be attained with small retinal motions or a slight jiggling of the paper and is robust over large changes in the patterns, frequencies and boundary shapes. In this paper, we explain that the cause of the illusion lies in the statistical difficulty of integrating local one-dimensional motion signals into two-dimensional image velocity measurements. The estimation of image velocity generally is biased, and for the particular spatial gradient distributions of the Ouchi pattern the bias is highly pronounced, giving rise to a large difference in the velocity estimates in the two regions. The computational model introduced to describe the statistical estimation of image velocity also accounts for the findings of psychophysical studies with variations of the Ouchi pattern and for various findings on the perception of moving plaids. The insight gained from this computational study challenges the current models used to explain biological vision systems and to construct robotic vision systems. Considering the statistical difficulties in image velocity estimation in conjunction with the problem of discontinuity detection in motion fields suggests that theoretically the process of optical flow computations should not be carried out in isolation but in conjunction with the higher level processes of 3D motion estimation, segmentation and shape computation.},
	keywords = {Bias, MOTION, optical flow, Plaid, Statistics},
	isbn = {0042-6989},
	doi = {10.1016/S0042-6989(99)00162-5},
	url = {http://www.sciencedirect.com/science/article/pii/S0042698999001625},
	author = {Ferm{\"u}ller, Cornelia and Pless,Robert and Aloimonos, J.}
}
@conference {14267,
	title = {The statistics of optical flow: implications for the process of correspondence in vision},
	booktitle = {15th International Conference on Pattern Recognition, 2000. Proceedings},
	volume = {1},
	year = {2000},
	month = {2000///},
	pages = {119-126 vol.1 - 119-126 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {This paper studies the three major categories of flow estimation methods: gradient-based, energy-based, and correlation methods; it analyzes different ways of compounding 1D motion estimates (image gradients, spatio-temporal frequency triplets, local correlation estimates) into 2D velocity estimates, including linear and nonlinear methods. Correcting for the bias would require knowledge of the noise parameters. In many situations, however, these are difficult to estimate accurately, as they change with the dynamic imagery in unpredictable and complex ways. Thus, the bias really is a problem inherent to optical flow estimation. We argue that the bias is also integral to the human visual system. It is the cause of the illusory perception of motion in the Ouchi pattern and also explains various psychophysical studies of the perception of moving plaids. Finally, the implication of the analysis is that flow or correspondence can be estimated very accurately only when feedback is utilized},
	keywords = {Bias, Computer vision, correlation, correlation methods, energy-based method, flow estimation, Frequency estimation, gradient method, gradient methods, Image analysis, Image motion analysis, Image sequences, least squares, least squares approximations, Motion estimation, Nonlinear optics, Optical feedback, optical flow, Optical harmonic generation, Optical noise, Statistics, Visual perception},
	isbn = {0-7695-0750-6},
	doi = {10.1109/ICPR.2000.905288},
	author = {Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
