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Search Publications by: Afzal A. Godil (Fed)

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Displaying 1 - 25 of 74

The Text Recognition Algorithm Independent Evaluation (TRAIT)

December 15, 2017
Author(s)
Afzal A. Godil, Patrick J. Grother, Mei L. Ngan
The report describes and presents the results for text detection and recognition (TRAIT) evaluation in support of forensic investigations of digital media. These im- ages are of interest to NIST’s partner law enforcement agencies that seek to employ text

SHREC'17 Track: Point-Cloud Shape Retrieval of Non-Rigid Toys

December 14, 2017
Author(s)
Afzal A. Godil
In this paper, we present the results of the SHREC'17 Track: Point-Cloud Shape Retrieval of Non-Rigid Toys. The aim of this track is to create a fair benchmark to evaluate the performance of methods on the non-rigid point- cloud shape retrieval problem

Compressed Volume Rendering using Deep Learning

October 2, 2017
Author(s)
Wesley N. Griffin, Afzal A. Godil, Jeffrey W. Bullard, Judith E. Terrill, Amitabh Varshney, Somay Jain
Scientific simulations often generate large amounts of multivariate time varying volumetric data. Visualizing these volumes is essential for understanding the underlying scientific processes which generate this data. In this paper, we present a method to

Shape Retrieval of Non-Rigid 3D Human Models

April 26, 2016
Author(s)
Afzal A. Godil, David Pickup
3D models of humans are commonly used within computer graphics and vision, and so the ability to distinguish between body shapes is an important shape retrieval problem. We extend our recent paper which provided a benchmark for testing non-rigid 3D shape

SHREC'15: Range Scans based 3D Shape Retrieval

May 3, 2015
Author(s)
Afzal A. Godil
The objective of the SHREC'15 Range Scans based 3D Shape Retrieval track is to evaluate algorithms that match range scans of real objects to complete 3D mesh models in a target dataset. The task is to retrieve a rank list of complete 3D models that are of

Performance Metrics for Evaluating Object and Human Detection and Tracking Systems

July 30, 2014
Author(s)
Afzal A. Godil, Roger Bostelman, William P. Shackleford, Tsai H. Hong, Michael O. Shneier
In this report, we provide an overview of various performance evaluation metrics for object detection and tracking for robot safety applications in smart manufacturing. We present four different types of performance evaluation metrics based on detection

SHREC’14 Track: Extended Large Scale Sketch-Based 3D Shape Retrieval

June 12, 2014
Author(s)
Afzal A. Godil, Chunyuan Li
Large scale sketch-based 3D shape retrieval has received more and more attentions in the community of content- based 3D object retrieval. The objective of this track is to evaluate the performance of different sketch-based 3D model retrieval algorithms

SHREC’14 Track: Large Scale Comprehensive 3D Shape Retrieval

June 12, 2014
Author(s)
Afzal A. Godil, Chunyuan Li
The objective of this track is to evaluate the performance of 3D shape retrieval approaches on a large-sale com- prehensive 3D shape database which contains different types of models, such as generic, articulated, CAD and architecture models. The track is

SHREC’14 Track: Retrieval and classification on Textured 3D Models

June 12, 2014
Author(s)
Afzal A. Godil
This contribution reports the results of the SHREC 2014 track: Retrieval and classification on textured 3D models, whose goal is to evaluate the performance of retrieval algorithms when models vary either by geometric shape or texture, or both. The

SHREC’14 Track: Shape Retrieval of Non-Rigid 3D Human Models

June 12, 2014
Author(s)
Afzal A. Godil, Chunyuan Li
We have created a new benchmarking dataset for testing non-rigid 3D shape retrieval algorithms, one that is much more challenging than existing datasets. Our dataset features exclusively human models, in a variety of body shapes and poses. 3D models of

A comparison of methods for sketch-based 3D shape retrieval

December 13, 2013
Author(s)
Afzal A. Godil
Sketch-based 3D shape retrieval has become an important research topic in content-based 3D object retrieval. To foster this research area, two Shape Retrieval Contest (SHREC) tracks on this topic have been organized by us in 2012 and 2013 based on a small

3D Ground-Truth Systems for Object/Human Recognition and Tracking

June 28, 2013
Author(s)
Afzal A. Godil, Roger V. Bostelman, Kamel Saidi, William P. Shackleford, Geraldine Cheok, Michael O. Shneier, Tsai H. Hong
We have been researching 3D ground-truth systems for performance evaluation of vision and perception systems in the fields of smart manufacturing and robotics safety. In this paper we first present an overview of different systems that have been used to

SHREC’13 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