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Displaying records 11 to 20 of 30 records.
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11. An evaluation of local shape descriptors for 3D shape retrieval
Topic: Data Mining
Published: 9/26/2012
Authors: Afzal A Godil, Sarah Y. Tang
Abstract: 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. H ...

12. Overview of the TREC-2010 Blog Track
Topic: Data Mining
Published: 8/15/2012
Authors: Ian M Soboroff, Iadh Ounis, Craig Macdonald
Abstract: The Blog track aims to investigate the information seeking behavior in the blogosphere. The track was initiated in 2006, and has used an incremental approach in tackling several search tasks by their level of difficulty. In TREC 2010, the track has i ...

13. Feature-preserved 3D Canonical Form
Topic: Data Mining
Published: 7/28/2012
Authors: Afzal A Godil, Zhouhui Lian
Abstract: 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 ...

14. Evaluation of 3D Interest Point Detection Techniques via Human-generated Ground Truth
Topic: Data Mining
Published: 6/29/2012
Authors: Afzal A Godil, Helin Dutagaci
Abstract: In this paper, we present an evaluation strategy based on human-generated ground truth to measure the performance of 3D interest point detection techniques. We provide quantitative evaluation measures that relate automatically detected interest point ...

15. A New Convexity Measurement for 3D Meshes
Topic: Data Mining
Published: 6/16/2012
Authors: Afzal A Godil, Zhouhui Lian
Abstract: 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 edg ...

16. SHREC‰12 Track: Generic 3D Shape Retrieval
Topic: Data Mining
Published: 5/13/2012
Authors: Bo Li, Afzal A Godil
Abstract: 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 participant ...

17. An Evaluation of Local Shape Descriptors for 3D Shape Retrieval
Series: NIST Interagency/Internal Report (NISTIR)
Report Number: 7812
Topic: Data Mining
Published: 3/8/2012
Author: Sarah Y. Tang
Abstract: 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 t ...

18. Versus: A Framework for General Content-Based Comparisons
Topic: Data Mining
Published: 12/5/2011
Authors: Peter Bajcsy, Antoine Vandecreme, Benjamin J Long, Paul Khouri Saba, Joe Chalfoun, Luigi Marini, Devin Bonnie, Rob Kooper, Michal Ondrejcek, Kenton McHenry
Abstract: Abstract,We present a framework for the execution and dissemination of customizable content-based file comparison methods. Given digital objects such as files, database entries, or in-memory data structures, we are interested in establishing thei ...

19. Toward Privacy Standards Based on Empirical Studies
Topic: Data Mining
Published: 4/28/2011
Authors: Serge M. (Serge) Egelman, Erika McCallister
Abstract: In this paper, we argue that if privacy standards are created to guide ,do-not-trackŠ technologies, it is imperative that these standards are created with the primary stakeholder in mind: the data subject. Previous privacy and security standards ha ...

20. Salient Local 3D Features for 3D Shape Retrieval
Topic: Data Mining
Published: 4/7/2011
Authors: Afzal A Godil, Asim Wagan
Abstract: 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 ...

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