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Mathematics & Statistics

Image & signal processing

Search Publications

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  • Published Date
Displaying 226 - 250 of 311

SHREC12 Track: Generic 3D Shape Retrieval

May 13, 2012
Author(s)
Bo Li, Afzal A. Godil
Generic 3D shape retrieval is a fundamental research area in the field of content-based 3D model retrieval. The aim of this track is to measure and compare the performance of generic 3D shape retrieval methods implemented by different participants over the

SHREC12 Track: Sketch-Based 3D Shape Retrieval

May 13, 2012
Author(s)
Bo Li, Afzal A. Godil
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 implemented by different participants

An Evaluation of Local Shape Descriptors for 3D Shape Retrieval

March 8, 2012
Author(s)
Sarah Y. Tang
As the usage of 3D models increases, so does the importance of developing accurate 3D shape retrieval algorithms. Most prominently, shape descriptors are used to describe the geometric and topological properties of objects and compared to determine two

Objective Evaluation of Imager Performance

December 1, 2011
Author(s)
Francine K. Amon, Dennis D. Leber, Nicholas Paulter
We describe a method by which the evaluation and characterization of the performance of an imager can be done objectively and scientifically, that is, without routine operator interpretation. Although this method is demonstrated herein for passive long

Integrating jQuery with the 3D Descriptive Markup of X3DOM

October 31, 2011
Author(s)
Sanford P. Ressler
This paper describes a number of techniques using jQuery to take advantage of the 3D descriptive markup implemented by X3DOM. X3DOM is a project of the Web3D Consortium, primarily being implemented by staff at Fraunhoffer IGD to provide 3D descriptive

SHREC11 Track: Generic Shape Retrieval

April 14, 2011
Author(s)
Helin Dutagaci, Afzal A. Godil
In this paper we present the results of the 3D Shape Retrieval Contest 2011 (SHREC’11) track on generic shape retrieval. The aim of this track is to evaluate the performance of 3D shape retrieval algorithms that can operate on arbitrary 3D models. The

Evaluation of 3D Interest Point Detection Techniques

April 7, 2011
Author(s)
Helin Dutagaci, Chun Pan (Benny) Cheung, Afzal A. Godil
In this paper, we compare the results of five 3D interest point detection techniques to the interest points marked by human subjects. This comparison is used to quantitatively evaluate the interest point detection algorithms. We asked human subjects to

Salient Local 3D Features for 3D Shape Retrieval

April 7, 2011
Author(s)
Afzal A. Godil, Asim Wagan
In this paper we describe a new formulation for the 3D salient local features based on the voxel grid inspired by the Scale Invariant Feature Transform (SIFT). We use it to identify the salient keypoints (invariant points) on a 3D voxelized model and

Efficient Motion Vector Interpolation for Error Concealment of H.264/AVC

March 1, 2011
Author(s)
Hamid Gharavi
In video communications the compressed video stream is very likely to be corrupted by channel errors. In order to combat these channel errors, many methods have been proposed. In this paper, a new method for motion vectors (MVs) interpolation with the help

A Benchmark for Best View Selection of 3D Objects

December 23, 2010
Author(s)
Helin Dutagaci, Chun Pan (Benny) Cheung, Afzal A. Godil
The best view selection corresponds to the task of automatically selecting the most representative view of a 3D model. In this paper, we describe a benchmark for evaluation of best view selection algorithms. The benchmark consists of the preferred views of

Benchmarks, Performance Evaluation and Contests for 3D Shape Retrieval

December 20, 2010
Author(s)
Afzal A. Godil, Zhouhui Lian, Helin Dutagaci
Benchmarking of 3D Shape retrieval allows developers and researchers to compare the strengths of different algorithms on a standard dataset. Here we discuss the different steps involved in developing a benchmark and some of the issues involved. We then

Image Classification of Vascular Smooth Muscle Cells

November 11, 2010
Author(s)
Michael Grasso, Ronil Mokashi , Alden A. Dima, Antonio Cardone, Kiran Bhadriraju, Anne L. Plant, Mary C. Brady, Yaacov Yesha, Yelena Yesha
The traditional method of cell microscopy can be subjective, due to observer variability, a lack of standardization, and a limited feature set. To address this challenge, we developed an image classifier using a machine learning approach. Our system was

Data Sets for the Qualification of Volumetric CT as a Quantitative Imaging Biomarker in Lung Cancer

October 20, 2010
Author(s)
Charles D. Fenimore, Andrew Buckler, Lawrence H. Schwartz, Nicholas Petrick, Michael McNitt-Gray, Binsheng Zhao, Anthony P. Reeves, P. David Mozeley, Ricardo S. Avila
The drug development industry is faced with increasing costs and decreasing success rates. New ways to understand biology as well as the increasing interest in personalized treatments for smaller patient segments requires new capabilities for the rapid

PYRAMID MODEL BASED DOWN-SAMPLING FOR IMAGE INPAINTING

September 2, 2010
Author(s)
Hamid Gharavi
Image inpainting is a useful and powerful technique for automatically restoring or removing objects in films and damaged pictures. In the last ten years, many excellent inpainting algorithms have been proposed after Bertalmio et al. [1]. However, no paper

An Integrated Interactive Visualization and Analysis Environment to study the Impact of Fire on Building Structures

July 25, 2010
Author(s)
Dilip K. Banerjee, John L. Gross, Pradeep R. Gaddam, Thomas M. Olano, William J. Hess, Judith E. Terrill, Terence J. Griffin, John G. Hagedorn, John T. Kelso, Steven G. Satterfield
We have created an integrated interactive visualization and analysis environment, that can be used immersively or on the desktop, to study the interaction among fire, heat transfer, and structural deformation computed from three linked simulations. In this

Investigating the Bag-of-Words Method for 3D Shape Retrieval

June 30, 2010
Author(s)
Afzal A. Godil, Xiaolan Li
This paper investigates the capabilities of the Bag-of-Words (BW) method in the 3D shape retrieval field. The contributions of this paper are: 1) the 3D shape retrieval task is categorized from different points of view: specific vs. generic, partial-to

Precision and Accuracy in Scientific Imaging

May 18, 2010
Author(s)
Russell A. Kirsch
Digital images are commonly used to represent scientific data. Typically, high resolution images with many square pixels are considered to be necessary under the assumption that the increased precision of such images yields increased accuracy to the viewer
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