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Search Publications

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  • Published Date
Displaying 201 - 225 of 311

Shape Calculus for Shape Energies in Image Processing

July 22, 2013
Author(s)
Gunay Dogan, Ricardo H. Nochetto
Many image processing problems are naturally expressed as energy minimization or shape optimization problems, in which the free variable is a shape, such as a curve in 2d or a surface in 3d. Examples are image segmentation, multiview stereo reconstruction

SHREC13 Track: Large Scale Sketch-Based 3D Shape Retrieval

June 6, 2013
Author(s)
Afzal A. Godil, Bo Li , Yijuan Lu, Tobias Schreck
Sketch-based 3D shape retrieval has become an important research topic in content-based 3D object retrieval. The aim of this track is to measure and compare the performance of sketch-based 3D shape retrieval methods based on a large scale hand-drawn sketch

In-plane Rotation and Scale Invariant Clustering and Dictionary Learning

June 3, 2013
Author(s)
P J. Phillips, Challa Sastry, Yi-Chen Chen, Vishal M. Patel, Rama Chellappa
n this paper, we present an approach that simulta- neously clusters images and learns dictionaries from the clusters. The method learns dictionaries in the Radon transform domain, while clustering in the image domain. The main feature of the proposed

Dictionary Learning from Ambiguously Labeled Data

April 9, 2013
Author(s)
P J. Phillips, Yi-Chen Chen, Vishal M. Patel, Jaishanker K. Pillai, Rama Chellappa
We propose a novel dictionary-based learning method for ambiguously labeled multiclass classification, where each training sample has multiple labels and only one of them is the correct label. The dictionary learning problem is solved using an iterative

A Hybrid CPU-GPU Approach to Fourier-Based Image Stitching of Optical Microscopy Images

March 3, 2013
Author(s)
Walid Keyrouz, Timothy J. Blattner, Bertrand C. Stivalet, Joe Chalfoun, Mary C. Brady, Shujia Zhou
We present a hybrid CPU-GPU approach for the Fourier-based stitching of optical microscopy images. This system achieves sub-minute stitching rates with large grids; it stitches a grid of 59x42 tiles in 26 seconds on a two-CPU (8 physical cores) & two-GPU

Declarative Integration of Interactive 3D Graphics into the World-Wide Web: Principles, Current Approaches, and Research Agenda

February 10, 2013
Author(s)
Jacek Jankowski, Johannes Behr, Yvonne Jung, Kristian Sons, Philipp Slusallek, Sanford P. Ressler
With the advent of WebGL, plugin-free hardware-accelerated interactive 3D graphics has finally arrived in all major Web browsers. WebGL is an imperative solution that is tied to the functionality of rasterization APIs. Consequently, its usage requires a

Segmenting Time-lapse Phase Contrast Images of Adjacent NIH 3T3 Cells

January 15, 2013
Author(s)
Joe Chalfoun, Alden A. Dima, Marcin Kociolek, Michael W. Halter, Antonio Cardone, Adele P. Peskin, Peter Bajcsy, Mary C. Brady
We present a new method for segmenting phase contrast images of NIH 3T3 fibroblast cells that is accurate even when cells are in contact. The problem of segmentation, when cells are in contact, poses a challenge to the accurate automation of cell counting

How to Select Microscopy Image Similarity Metrics?

October 10, 2012
Author(s)
Peter Bajcsy, Joe Chalfoun, Mary C. Brady
Comparisons of two microscopy images can be accomplished in many different ways. This paper presents a system that recommends appropriate similarity metrics for microscopy image comparisons based on biological application requirements. The motivation stems

A comparison of methods for Non-rigid 3D shape retrieval

September 26, 2012
Author(s)
Zhouhui Lian, Afzal A. Godil
Non-rigid 3D shape retrieval has become an active and important research topic in content-based 3D object retrieval. The aim of this paper is to measure and compare the performance of state-of-the-art methods for non-rigid 3D shape retrieval. The paper

An evaluation of local shape descriptors for 3D shape retrieval

September 26, 2012
Author(s)
Afzal A. Godil, Sarah Y. Tang
As the usage of 3D models increases, so does the importance of developing accurate 3D shape retrieval algorithms. A common approach is to calculate a shape descriptor for each object, which can then be compared to determine two objects’ similarity. However

Big Data Issues in Quantitative Imaging

August 29, 2012
Author(s)
Mary C. Brady, Alden A. Dima, Charles D. Fenimore, James J. Filliben, John Lu, Adele Peskin, Mala Ramaiah, Ganesh Saiprasad, Ram D. Sriram

An Exploration of the Operational Ramifications of Lossless Compression of 1000 ppi Fingerprint Imagery

August 6, 2012
Author(s)
Shahram Orandi, John M. Libert, John D. Grantham, Kenneth Ko, Stephen S. Wood, Jin Chu Wu, Lindsay M. Petersen, Bruce Bandini
This paper presents the findings of a study initially conducted to measure the operational impact of JPEG 2000 lossy compression on 1000 ppi fingerprint imagery at various levels of compression, but later expanded to include lossless compression. Lossless

Not Your Mother's Web3D: Integrating X3DOM, jQuery and HTML5

August 4, 2012
Author(s)
Sanford P. Ressler
This tutorial, for intermediate users, is suitable for educators, scientists and artists, with some 3D and programming experience, (all attendees). The benefits of declarative 3D markup, as realized by X3DOM will be emphasized in the context of integration

Feature-preserved 3D Canonical Form

July 28, 2012
Author(s)
Afzal A. Godil, Zhouhui Lian
Abstract Measuring the dissimilarity between non-rigid objects is a challenging problem in 3D shape retrieval. One potential solution is to construct the models’ 3D canonical forms (i.e., isometry-invariant representations in 3D Euclidean domain) on which

A New Convexity Measurement for 3D Meshes

June 16, 2012
Author(s)
Afzal A. Godil, Zhouhui Lian
This paper presents a novel convexity measurement for 3D meshes. The new convexity measure is calculated by minimizing the ratio of the summed area of valid regions in a mesh’s six views, which are projected on faces of the bounding box whose edges are

Grand Challenges of Measurement Science with Big Data

June 14, 2012
Author(s)
Peter Bajcsy
This presentation discusses Grand Challenges of Measurement Science with Big Data. It illustrates the difference between Measurement Science with Little Data and Big Data in the domain of cell biology and microscopy image observations.
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