Search results for: John W. Fisher

Items from 1 to 20 out of 64 results

article

The Manhattan Frame Model—Manhattan World Inference in the Space of Surface Normals

Julian Straub, Oren Freifeld, Guy Rosman, John J. Leonard, more

IEEE Transactions on Pattern Analysis and Machine Intelligence > 2018 > 40 > 1 > 235 - 249

Objects and structures within man-made environments typically exhibit a high degree of organization in the form of orthogonal and parallel planes. Traditional approaches utilize these regularities via the restrictive, and rather local, Manhattan World (MW) assumption which posits that every plane is perpendicular to one of the axes of a single coordinate system. The aforementioned regularities are...

article

A Bayesian state-space approach for damage detection and classification

Zoran Dzunic, Justin G. Chen, Hossein Mobahi, Oral Büyüköztürk, more

Mechanical Systems and Signal Processing > 2017 > 96 > C > 239-259

The problem of automatic damage detection in civil structures is complex and requires a system that can interpret collected sensor data into meaningful information. We apply our recently developed switching Bayesian model for dependency analysis to the problems of damage detection and classification. The model relies on a state-space approach that accounts for noisy measurement processes and missing...

chapter

Efficient Global Point Cloud Alignment Using Bayesian Nonparametric Mixtures

Julian Straub, Trevor Campbell, Jonathan P. How, John W. Fisher

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) > 2403 - 2412

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Point cloud alignment is a common problem in computer vision and robotics, with applications ranging from 3D object recognition to reconstruction. We propose a novel approach to the alignment problem that utilizes Bayesian nonparametrics to describe the point cloud and surface normal densities, and branch and bound (BB) optimization to recover the relative transformation. BB uses a novel, refinable,...

chapter

On the Role of Representations for Reasoning in Large-Scale Urban Scenes

Randi Cabezas, Maros Blaha, Sue Zheng, Guy Rosman, more

2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) > 1514 - 1523

2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

The advent of widely available photo collections covering broad geographic areas has spurred significant advances in large-scale urban scene modeling. While much emphasis has been placed on reconstruction and visualization, the utility of such models extends well beyond. Specifically, these models should support a wide variety of reasoning tasks (or queries), and thus enable advanced scene study....

chapter

A Unified Variational Approach to Denoising and Bias Correction in MR

Ayres Fan, William M. Wells, John W. Fisher, Müjdat Çetin, more

Lecture Notes in Computer Science > Information Processing in Medical Imaging > Posters I: Shape Modelling and Analysis > 148-159

We propose a novel bias correction method for magnetic resonance (MR) imaging that uses complementary body coil and surface coil images. The former are spatially homogeneous but have low signal intensity; the latter provide excellent signal response but have large bias fields. We present a variational framework where we optimize an energy functional to estimate the bias field and the underlying image...

chapter

Maximum Mutual Information Principle for Dynamic Sensor Query Problems

Emre Ertin, John W. Fisher, Lee C. Potter

Lecture Notes in Computer Science > Information Processing in Sensor Networks > Information Processing in Sensor Networks > 405-416

In this paper we study a dynamic sensor selection method for Bayesian filtering problems. In particular we consider the distributed Bayesian Filtering strategy given in [1] and show that the principle of mutual information maximization follows naturally from the expected uncertainty minimization criterion in a Bayesian filtering framework. This equivalence results in a computationally feasible approach...

chapter

Information-Driven Adaptive Structured-Light Scanners

Guy Rosman, Daniela Rus, John W. Fisher

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) > 874 - 883

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Sensor planning and active sensing, long studied in robotics, adapt sensor parameters to maximize a utility function while constraining resource expenditures. Here we consider information gain as the utility function. While these concepts are often used to reason about 3D sensors, these are usually treated as a predefined, black-box, component. In this paper we show how the same principles can be...

chapter

Hypothesis Testing over Factorizations for Data Association

Alexander T. Ihler, John W. Fisher, Alan S. Willsky

Lecture Notes in Computer Science > Information Processing in Sensor Networks > Information Processing in Sensor Networks > 239-253

The issue of data association arises frequently in sensor networks; whenever multiple sensors and sources are present, it may be necessary to determine which observations from different sensors correspond to the same target. In highly uncertain environments, one may need to determine this correspondence without the benefit of an a priori known joint signal/sensor model. This paper examines the data...

chapter

Incorporating Spatial Priors into an Information Theoretic Approach for fMRI Data Analysis

Junmo Kim, John W. Fisher, Andy Tsai, Cindy Wible, more

Lecture Notes in Computer Science > Medical Image Computing and Computer-Assisted Intervention – MICCAI 2000 > Neuroimaging and Neurosurgery > 62-71

In previous work a novel information-theoretic approach was introduced for calculating the activation map for fMRI analysis [Tsai et al, 1999]. In that work the use of mutual information as a measure of activation resulted in a nonparametric calculation of the activation map. Nonparametric approaches are attractive as the implicit assumptions are milder than the strong assumptions of popular approaches...

chapter

Geometric and Statistical Approaches to Audiovisual Segmentation

Trevor Darrell, John W. Fisher, Kevin W. Wilson, Michael R. Siracusa

Text, Speech and Language Technology > Advances in Natural Multimodal Dialogue Systems > Annotation and Analysis of Multimodal Data: Speech and Gesture > 159-180

Multimodal approaches are proposed for segmenting multiple speakers using geometric or statistical techniques. When multiple microphones and cameras are available, 3-D audiovisual tracking is used for source segmentation and array processing. With just a single camera and microphone, an information theoretic criteria separates speakers in a video sequence and associates relevant portions of the audio...

chapter

Exact MAP Activity Detection in fMRI Using a GLM with an Ising Spatial Prior

Eric R. Cosman, John W. Fisher, William M. Wells

Lecture Notes in Computer Science > Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004 > Brain Imaging Applications > 703-710

Previous work [5] has shown how Ising spatial priors [1] can be incorported into fMRI analysis in a principled manner by using Mutual Information as a statistic for protocol-related activity. The activation image with maximum a posteriori (MAP) probability can then be computed exactly in polynomial time by reduction to a Min-Cut/Max-Flow Problem [4]. In this work, we show that an Ising prior can be...

chapter

Combining Simple Models to Approximate Complex Dynamics

Leonid Taycher, John W. Fisher, Trevor Darrell

Lecture Notes in Computer Science > Statistical Methods in Video Processing > Tracking > 94-104

Stochastic tracking of structured models in monolithic state spaces often requires modeling complex distributions that are difficult to represent with either parametric or sample-based approaches. We show that if redundant representations are available, the individual state estimates may be improved by combining simpler dynamical systems, each of which captures some aspect of the complex behavior...

chapter

Analysis of Functional MRI Data Using Mutual Information

Andy Tsai, John W. Fisher, Cindy Wible, William M. Wells, more

Lecture Notes in Computer Science > Medical Image Computing and Computer-Assisted Intervention – MICCAI’99 > Spatiotemporal and Diffusion Tensor Analysis > 473-480

A new information-theoretic approach is presented for analyzing fMRI data to calculate the brain activation map. The method is based on a formulation of the mutual information between two waveforms-the fMRI temporal response of a voxel and the experimental protocol timeline. Scores based on mutual information are generated for all voxels and then used to compute the activation map of an experiment...

chapter

Probabalistic Models and Informative Subspaces for Audiovisual Correspondence

John W. Fisher, Trevor Darrell

Lecture Notes in Computer Science > Computer Vision — ECCV 2002 > Texture Shading and Colour / Grouping and Segmentation / Object Recognition > 592-603

We propose a probabalistic model of single source multi-modal generation and show how algorithms for maximizing mutual information can find the correspondences between components of each signal. We show how non-parametric techniques for finding informative subspaces can capture the complex statistical relationship between signals in different modalities. We extend a previous technique for finding...

chapter

Audio-visual Segmentation and “The Cocktail Party Effect”

Trevor Darrell, John W. Fisher, Paul Viola

Lecture Notes in Computer Science > Advances in Multimodal Interfaces — ICMI 2000 > Affective and Perceptual Computing > 32-40

Audio-based interfaces usually suffer when noise or other acoustic sources are present in the environment. For robust audio recognition, a single source must first be isolated. Existing solutions to this problem generally require special microphone configurations, and often assume prior knowledge of the spurious sources. We have developed new algorithms for segmenting streams of audio-visual information...

chapter

MCMC Curve Sampling for Image Segmentation

Ayres C. Fan, John W. Fisher, William M. Wells, James J. Levitt, more

Lecture Notes in Computer Science > Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007 > General Medical Image Computing - III > 477-485

We present an algorithm to generate samples from probability distributions on the space of curves. We view a traditional curve evolution energy functional as a negative log probability distribution and sample from it using a Markov chain Monte Carlo (MCMC) algorithm. We define a proposal distribution by generating smooth perturbations to the normal of the curve and show how to compute the transition...

chapter

Face Recognition from Long-Term Observations

Gregory Shakhnarovich, John W. Fisher, Trevor Darrell

Lecture Notes in Computer Science > Computer Vision — ECCV 2002 > Texture Shading and Colour / Grouping and Segmentation / Object Recognition > 851-865

We address the problem of face recognition from a large set of images obtained over time - a task arising in many surveillance and authentication applications. A set or a sequence of images provides information about the variability in the appearance of the face which can be used for more robust recognition. We discuss different approaches to the use of this information, and show that when cast as...

chapter

A Unified Statistical and Information Theoretic Framework for Multi-modal Image Registration

Lilla Zöllei, John W. Fisher, William M. Wells

Lecture Notes in Computer Science > Information Processing in Medical Imaging > Registration – Modelling Similarity > 366-377

We formulate and interpret several registration methods in the context of a unified statistical and information theoretic framework. A unified interpretation clarifies the implicit assumptions of each method yielding a better understanding of their relative strengths and weaknesses. Additionally, we discuss a generative statistical model from which we derive a novel analysis tool, the auto-information function...

chapter

Understanding and Assessing Spiritual Health

John W. Fisher

International Handbooks of Religion and Education > International Handbook of Education for Spirituality, Care and Wellbeing > The Psychology of Religion and Spirituality: Implications for Education and Wellbeing – An Introduction > 69-88

Attempts at defining spirituality vacillate between the human and the divine. However, many studies show relationships between spirituality or religion and health. An extensive literature search and a study of almost 100 educators in four different types of schools led to a model in which spiritual health is understood to be a, if not the, fundamental dimension of health, permeating and integrating...

chapter

Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple

Oren Freifeld, Soren Hauberg, Kayhan Batmanghelich, John W. Fisher

2015 IEEE International Conference on Computer Vision (ICCV) > 2911 - 2919

2015 IEEE International Conference on Computer Vision (ICCV)

We propose novel finite-dimensional spaces of Rn ? Rn transformations, n ? {1, 2, 3}, derived from (continuously-defined) parametric stationary velocity fields. Particularly, we obtain these transformations, which are diffeomorphisms, by fast and highly-accurate integration of continuous piecewise-affine velocity fields, we also provide an exact solution for n = 1. The simple-yet-highly-expressive...

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THREE-DIMENSIONAL DISPLAYS (4)
TRACKING (4)
CAMERAS (3)
ESTIMATION (3)
GRAPHICAL MODELS (3)
HIDDEN MARKOV MODELS (3)
SENSORS (3)
APPROXIMATION METHODS (2)
BAYESIAN INFERENCE (2)
COMPUTATIONAL MODELING (2)
CURRENT MEASUREMENT (2)
DATA MODELS (2)
EYSENCK (2)
IMAGE SEGMENTATION (2)
MANHATTAN WORLD (2)
MUTUAL INFORMATION (2)
OPTIMIZATION (2)
PERSONALITY (2)
PIXEL (2)
PLANNING (2)
PRAYER (2)
SEQUENTIAL DECISION PROCEDURES (2)
SEQUENTIAL ESTIMATION (2)
SPIRITUAL WELL-BEING (2)
SPIRITUAL WELL-BEING QUESTIONNAIRE (2)
SURFACE TREATMENT (2)
TIME MEASUREMENT (2)
ACTIVE LEARNING (1)
ADAPTATION MODEL (1)
ADAPTATION MODELS (1)
ADDITIVES (1)
ADOLESCENTS (1)
AERIAL (1)
ANISOTROPY (1)
ANISOTROPY DETERMINATION (1)
APPROXIMATE MODELS (1)
APPROXIMATION ALGORITHMS (1)
ARTICULATED BODY TRACKING (1)
ARTIFICIAL NEURAL NETWORKS (1)
ATR (1)
AUTOMATIC TARGET RECOGNITION (1)
BACKGROUND SUBTRACTION (1)
BANDWIDTH (1)
BAYES METHODS (1)
BAYESIAN MODEL (1)
BAYESIAN MODELS (1)
BEAM WEB ATTACHMENT (1)
BELIEF PROPAGATION (1)
BIOTERRORISM (1)
BIOTERRORISM SURVEILLANCE SYSTEM (1)
BOOSTING (1)
CANONICAL SCATTERING (1)
CLASSIFICATION (1)
COGNITION (1)
COMPLEXITY THEORY (1)
COMPUTATIONAL COMPLEXITY (1)
CONNECTION (1)
CONNECTIVITY (1)
CONTINUITY PLATES (1)
CORRELATION FILTERS (1)
COST FUNCTION (1)
COVARIANCE MATRICES (1)
CYCLIC TESTS (1)
DAMAGE DETECTION (1)
DATA ANALYTICS (1)
DATA MINING (1)
DATA WAREHOUSING (1)
DEPTH CAMERA CALIBRATION (1)
DIFFRACTION MEASUREMENT (1)
DISCRIMINATIVE TREES (1)
DUCTILITY (1)
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EXPERIMENTAL DESIGN (1)
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GENDER (1)
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HAPPINESS (1)
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IMAGE FORMATION (1)
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INFERENCE (1)
INFERENCE ALGORITHMS (1)
INFORMATION MEASURES (1)
INVARIANCE (1)
INVERSE PROBLEM (1)
INVERSE PROBLEMS (1)
IRT (1)
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INFONA - science communication portal

Search results for: John W. Fisher

The Manhattan Frame Model—Manhattan World Inference in the Space of Surface Normals

A Bayesian state-space approach for damage detection and classification

Efficient Global Point Cloud Alignment Using Bayesian Nonparametric Mixtures

On the Role of Representations for Reasoning in Large-Scale Urban Scenes

A Unified Variational Approach to Denoising and Bias Correction in MR

Maximum Mutual Information Principle for Dynamic Sensor Query Problems

Information-Driven Adaptive Structured-Light Scanners

Hypothesis Testing over Factorizations for Data Association

Incorporating Spatial Priors into an Information Theoretic Approach for fMRI Data Analysis

Geometric and Statistical Approaches to Audiovisual Segmentation

Exact MAP Activity Detection in fMRI Using a GLM with an Ising Spatial Prior

Combining Simple Models to Approximate Complex Dynamics

Analysis of Functional MRI Data Using Mutual Information

Probabalistic Models and Informative Subspaces for Audiovisual Correspondence

Audio-visual Segmentation and “The Cocktail Party Effect”

MCMC Curve Sampling for Image Segmentation

Face Recognition from Long-Term Observations

A Unified Statistical and Information Theoretic Framework for Multi-modal Image Registration

Understanding and Assessing Spiritual Health

Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple

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