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| Author | Fadi Dornaika; A.Assoum; Bogdan Raducanu | ||||
| Title | Automatic Dimensionality Estimation for Manifold Learning through Optimal Feature Selection | Type | Conference Article | ||
| Year | 2012 | Publication  |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop | Abbreviated Journal | |
| Volume | 7626 | Issue | Pages | 575-583 | |
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| Abstract | A very important aspect in manifold learning is represented by automatic estimation of the intrinsic dimensionality. Unfortunately, this problem has received few attention in the literature of manifold learning. In this paper, we argue that feature selection paradigm can be used to the problem of automatic dimensionality estimation. Besides this, it also leads to improved recognition rates. Our approach for optimal feature selection is based on a Genetic Algorithm. As a case study for manifold learning, we have considered Laplacian Eigenmaps (LE) and Locally Linear Embedding (LLE). The effectiveness of the proposed framework was tested on the face recognition problem. Extensive experiments carried out on ORL, UMIST, Yale, and Extended Yale face data sets confirmed our hypothesis. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-34165-6 | Medium | |
| Area | Expedition | Conference | SSPR&SPR | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DAR2012 | Serial | 2174 | ||
| Permanent link to this record | |||||
| Author | Bogdan Raducanu; Fadi Dornaika | ||||
| Title | Out-of-Sample Embedding by Sparse Representation | Type | Conference Article | ||
| Year | 2012 | Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop | Abbreviated Journal | |
| Volume | 7626 | Issue | Pages | 336-344 | |
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| Abstract | A critical aspect of non-linear dimensionality reduction techniques is represented by the construction of the adjacency graph. The difficulty resides in finding the optimal parameters, a process which, in general, is heuristically driven. Recently, sparse representation has been proposed as a non-parametric solution to overcome this problem. In this paper, we demonstrate that this approach not only serves for the graph construction, but also represents an efficient and accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. Experimental results conducted on some challenging datasets confirmed the robustness of our approach and its superiority when compared to existing techniques. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-34165-6 | Medium | |
| Area | Expedition | Conference | SSPR&SPR | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ RaD2012c | Serial | 2175 | ||
| Permanent link to this record | |||||
| Author | Sergio Vera; Debora Gil; Antonio Lopez; Miguel Angel Gonzalez Ballester | ||||
| Title | Multilocal Creaseness Measure | Type | Journal | ||
| Year | 2012 | Publication |
The Insight Journal | Abbreviated Journal | IJ |
| Volume | Issue | Pages | |||
| Keywords | Ridges, Valley, Creaseness, Structure Tensor, Skeleton, | ||||
| Abstract | This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission. | ||||
| Address | |||||
| Corporate Author | Alma IT Systems | Thesis | |||
| Publisher | Place of Publication | Editor | |||
| Language | english | Summary Language | english | Original Title | |
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| Area | Expedition | Conference | |||
| Notes | IAM;ADAS; | Approved | no | ||
| Call Number | IAM @ iam @ VGL2012 | Serial | 1840 | ||
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| Author | Michal Drozdzal; Petia Radeva; Santiago Segui; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria | ||||
| Title | System and Method for Improving a Discriminative Model | Type | Patent | ||
| Year | 2012 | Publication |
US 61/450,886 | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | |||||
| Address | Given Imaging | ||||
| Corporate Author | US Patent Office | Thesis | |||
| Publisher | Place of Publication | Editor | |||
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| Area | Expedition | Conference | |||
| Notes | MILAB; OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DRS2012a | Serial | 1896 | ||
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| Author | Michal Drozdzal; Petia Radeva; Santiago Segui; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria | ||||
| Title | System and method for automatic detection of in vivo contraction video sequences | Type | Patent | ||
| Year | 2012 | Publication |
US20120057766 | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | Publication date: 2012/3/8 | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | |||
| Notes | MILAB; OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DRS2012b | Serial | 2071 | ||
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| Author | Xavier Perez Sala; Laura Igual; Sergio Escalera; Cecilio Angulo | ||||
| Title | Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models | Type | Book Chapter | ||
| Year | 2012 | Publication |
Vision Robotics: Technologies for Machine Learning and Vision Applications | Abbreviated Journal | |
| Volume | Issue | 2 | Pages | 23-42 | |
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| Abstract | Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis. | ||||
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| Publisher | IGI-Global | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
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| Area | Expedition | Conference | |||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ PIE2012 | Serial | 2064 | ||
| Permanent link to this record | |||||
| Author | Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester | ||||
| Title | Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs | Type | Book Chapter | ||
| Year | 2012 | Publication |
Workshop on Computational and Clinical Applications in Abdominal Imaging | Abbreviated Journal | |
| Volume | 7029 | Issue | Pages | 223–230 | |
| Keywords | medial manifolds, abdomen. | ||||
| Abstract | Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations. |
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| Address | Toronto; Canada; | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Link | Place of Publication | Berlin | Editor | H. Yoshida et al |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Lecture Notes in Computer Science | Abbreviated Series Title | LNCS | |
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-28556-1 | Medium | |
| Area | Expedition | Conference | ABDI | ||
| Notes | IAM;MV | Approved | no | ||
| Call Number | IAM @ iam @ VGB2012 | Serial | 1834 | ||
| Permanent link to this record | |||||