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Author | Palaiahnakote Shivakumara; Anjan Dutta; Trung Quy Phan; Chew Lim Tan; Umapada Pal | ||||
Title | A Novel Mutual Nearest Neighbor based Symmetry for Text Frame Classification in Video | Type | Journal Article | ||
Year | 2011 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 44 | Issue | 8 | Pages | 1671-1683 |
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Abstract | In the field of multimedia retrieval in video, text frame classification is essential for text detection, event detection, event boundary detection, etc. We propose a new text frame classification method that introduces a combination of wavelet and median moment with k-means clustering to select probable text blocks among 16 equally sized blocks of a video frame. The same feature combination is used with a new Max–Min clustering at the pixel level to choose probable dominant text pixels in the selected probable text blocks. For the probable text pixels, a so-called mutual nearest neighbor based symmetry is explored with a four-quadrant formation centered at the centroid of the probable dominant text pixels to know whether a block is a true text block or not. If a frame produces at least one true text block then it is considered as a text frame otherwise it is a non-text frame. Experimental results on different text and non-text datasets including two public datasets and our own created data show that the proposed method gives promising results in terms of recall and precision at the block and frame levels. Further, we also show how existing text detection methods tend to misclassify non-text frames as text frames in term of recall and precision at both the block and frame levels. | ||||
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Language | Summary Language | Original Title | |||
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Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ SDP2011 | Serial | 1727 | ||
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Author | Jon Almazan; Alicia Fornes; Ernest Valveny | ||||
Title | A Non-Rigid Feature Extraction Method for Shape Recognition | Type | Conference Article | ||
Year | 2011 | Publication | 11th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 987-991 | ||
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Abstract | This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost. | ||||
Address | Beijing; China; September 2011 | ||||
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-0-7695-4520-2 | Medium | ||
Area | Expedition | Conference | ICDAR | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ AFV2011 | Serial | 1763 | ||
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Author | Fadi Dornaika; Jose Manuel Alvarez; Angel Sappa; Antonio Lopez | ||||
Title | A New Framework for Stereo Sensor Pose through Road Segmentation and Registration | Type | Journal Article | ||
Year | 2011 | Publication | IEEE Transactions on Intelligent Transportation Systems | Abbreviated Journal | TITS |
Volume | 12 | Issue | 4 | Pages | 954-966 |
Keywords | road detection | ||||
Abstract | This paper proposes a new framework for real-time estimation of the onboard stereo head's position and orientation relative to the road surface, which is required for any advanced driver-assistance application. This framework can be used with all road types: highways, urban, etc. Unlike existing works that rely on feature extraction in either the image domain or 3-D space, we propose a framework that directly estimates the unknown parameters from the stream of stereo pairs' brightness. The proposed approach consists of two stages that are invoked for every stereo frame. The first stage segments the road region in one monocular view. The second stage estimates the camera pose using a featureless registration between the segmented monocular road region and the other view in the stereo pair. This paper has two main contributions. The first contribution combines a road segmentation algorithm with a registration technique to estimate the online stereo camera pose. The second contribution solves the registration using a featureless method, which is carried out using two different optimization techniques: 1) the differential evolution algorithm and 2) the Levenberg-Marquardt (LM) algorithm. We provide experiments and evaluations of performance. The results presented show the validity of our proposed framework. | ||||
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1524-9050 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ DAS2011; ADAS @ adas @ das2011a | Serial | 1833 | ||
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Author | Mariano Vazquez; Ruth Aris; Guillaume Hozeaux; R.Aubry; P.Villar;Jaume Garcia ; Debora Gil; Francesc Carreras | ||||
Title | A massively parallel computational electrophysiology model of the heart | Type | Journal Article | ||
Year | 2011 | Publication | International Journal for Numerical Methods in Biomedical Engineering | Abbreviated Journal | IJNMBE |
Volume | 27 | Issue | Pages | 1911-1929 | |
Keywords | computational electrophysiology; parallelization; finite element methods | ||||
Abstract | This paper presents a patient-sensitive simulation strategy capable of using the most efficient way the high-performance computational resources. The proposed strategy directly involves three different players: Computational Mechanics Scientists (CMS), Image Processing Scientists and Cardiologists, each one mastering its own expertise area within the project. This paper describes the general integrative scheme but focusing on the CMS side presents a massively parallel implementation of computational electrophysiology applied to cardiac tissue simulation. The paper covers different angles of the computational problem: equations, numerical issues, the algorithm and parallel implementation. The proposed methodology is illustrated with numerical simulations testing all the different possibilities, ranging from small domains up to very large ones. A key issue is the almost ideal scalability not only for large and complex problems but also for medium-size meshes. The explicit formulation is particularly well suited for solving this highly transient problems, with very short time-scale. | ||||
Address | Swansea (UK) | ||||
Corporate Author | John Wiley & Sons, Ltd. | Thesis | |||
Publisher | John Wiley & Sons, Ltd. | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | IAM | Approved | no | ||
Call Number | IAM @ iam @ VAH2011 | Serial | 1198 | ||
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Author | Alicia Fornes; Volkmar Frinken; Andreas Fischer; Jon Almazan; G. Jackson; Horst Bunke | ||||
Title | A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors | Type | Conference Article | ||
Year | 2011 | Publication | Proceedings of the 2011 Workshop on Historical Document Imaging and Processing | Abbreviated Journal | |
Volume | Issue | Pages | 83-90 | ||
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Abstract | The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach. | ||||
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Publisher | ACM | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-4503-0916-5 | Medium | ||
Area | Expedition | Conference | HIP | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ FFF2011a | Serial | 1823 | ||
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Author | Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
Title | A Holistic Approach for the Detection of Media-Adventitia Border in IVUS | Type | Conference Article | ||
Year | 2011 | Publication | 14th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
Volume | 6893 | Issue | Pages | 401-408 | |
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Abstract | In this paper we present a methodology for the automatic detection of media-adventitia border (MAb) in Intravascular Ultrasound. A robust computation of the MAb is achieved through a holistic approach where the position of the MAb with respect to other tissues of the vessel is used. A learned quality measure assures that the resulting MAb is optimal with respect to all other tissues. The mean distance error computed through a set of 140 images is 0.2164 (±0.1326) mm. | ||||
Address | Toronto, Canada | ||||
Corporate Author | Thesis | ||||
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 | 978-3-642-23625-9 | Medium | |
Area | Expedition | Conference | MICCAI | ||
Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ CPG2011 | Serial | 1739 | ||
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Author | Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; I. Bardaji; Horst Bunke | ||||
Title | A Generic Framework for Median Graph Computation based on a Recursive Embedding Approach | Type | Journal Article | ||
Year | 2011 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
Volume | 115 | Issue | 7 | Pages | 919-928 |
Keywords | Median Graph, Graph Embedding, Graph Matching, Structural Pattern Recognition | ||||
Abstract | The median graph has been shown to be a good choice to obtain a represen- tative of a set of graphs. However, its computation is a complex problem. Recently, graph embedding into vector spaces has been proposed to obtain approximations of the median graph. The problem with such an approach is how to go from a point in the vector space back to a graph in the graph space. The main contribution of this paper is the generalization of this previ- ous method, proposing a generic recursive procedure that permits to recover the graph corresponding to a point in the vector space, introducing only the amount of approximation inherent to the use of graph matching algorithms. In order to evaluate the proposed method, we compare it with the set me- dian and with the other state-of-the-art embedding-based methods for the median graph computation. The experiments are carried out using four dif- ferent databases (one semi-artificial and three containing real-world data). Results show that with the proposed approach we can obtain better medi- ans, in terms of the sum of distances to the training graphs, than with the previous existing methods. | ||||
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Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | IAM @ iam @ FKV2011 | Serial | 1831 | ||
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Author | Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Xavier Jimenez ; Oscar Vilarroya; Petia Radeva | ||||
Title | A fully-automatic caudate nucleus segmentation of brain MRI: Application in volumetric analysis of pediatric attention-deficit/hyperactivity disorder | Type | Journal Article | ||
Year | 2011 | Publication | BioMedical Engineering Online | Abbreviated Journal | BEO |
Volume | 10 | Issue | 105 | Pages | 1-23 |
Keywords | Brain caudate nucleus; segmentation; MRI; atlas-based strategy; Graph Cut framework | ||||
Abstract | Background
Accurate automatic segmentation of the caudate nucleus in magnetic resonance images (MRI) of the brain is of great interest in the analysis of developmental disorders. Segmentation methods based on a single atlas or on multiple atlases have been shown to suitably localize caudate structure. However, the atlas prior information may not represent the structure of interest correctly. It may therefore be useful to introduce a more flexible technique for accurate segmentations. Method We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure. Results We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis. Conclusion CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD. |
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1475-925X | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ ISH2011 | Serial | 1882 | ||
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Author | Carme Julia; Felipe Lumbreras; Angel Sappa | ||||
Title | A Factorization-based Approach to Photometric Stereo | Type | Journal Article | ||
Year | 2011 | Publication | International Journal of Imaging Systems and Technology | Abbreviated Journal | IJIST |
Volume | 21 | Issue | 1 | Pages | 115-119 |
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Abstract | This article presents an adaptation of a factorization technique to tackle the photometric stereo problem. That is to recover the surface normals and reflectance of an object from a set of images obtained under different lighting conditions. The main contribution of the proposed approach is to consider pixels in shadow and saturated regions as missing data, in order to reduce their influence to the result. Concretely, an adapted Alternation technique is used to deal with missing data. Experimental results considering both synthetic and real images show the viability of the proposed factorization-based strategy. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 115–119, 2011. | ||||
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Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ JLS2011; ADAS @ adas @ | Serial | 1711 | ||
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Author | Bogdan Raducanu; Fadi Dornaika | ||||
Title | A Discriminative Non-Linear Manifold Learning Technique for Face Recognition | Type | Book Chapter | ||
Year | 2011 | Publication | Informatics Engineering and Information Science | Abbreviated Journal | |
Volume | 254 | Issue | 6 | Pages | 339-353 |
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Abstract | In this paper we propose a novel non-linear discriminative analysis technique for manifold learning. The proposed approach is a discriminant version of Laplacian Eigenmaps which takes into account the class label information in order to guide the procedure of non-linear dimensionality reduction. By following the large margin concept, the graph Laplacian is split in two components: within-class graph and between-class graph to better characterize the discriminant property of the data.
Our approach has been tested on several challenging face databases and it has been conveniently compared with other linear and non-linear techniques. The experimental results confirm that our method outperforms, in general, the existing ones. Although we have concentrated in this paper on the face recognition problem, the proposed approach could also be applied to other category of objects characterized by large variance in their appearance. |
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 1865-0929 | ISBN | 978-3-642-25482-6 | Medium | |
Area | Expedition | Conference | ICIEIS | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ RaD2011 | Serial | 1804 | ||
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Author | Patricia Marquez; Debora Gil; Aura Hernandez-Sabate | ||||
Title | A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth | Type | Conference Article | ||
Year | 2011 | Publication | IEEE International Conference on Computer Vision – Workshops | Abbreviated Journal | |
Volume | Issue | Pages | 2042-2049 | ||
Keywords | IEEE International Conference on Computer Vision – Workshops | ||||
Abstract | Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. | ||||
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Publisher | IEEE | Place of Publication | Barcelona (Spain) | Editor | |
Language | English | Summary Language | English | Original Title | |
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICCVW | ||
Notes | IAM; ADAS | Approved | no | ||
Call Number | IAM @ iam @ MGH2011 | Serial | 1682 | ||
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Author | Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez | ||||
Title | A Coarse-to-fine Approach for fast Deformable Object Detection | Type | Conference Article | ||
Year | 2011 | Publication | IEEE conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1353-1360 | ||
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Address | Colorado Springs; USA | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CVPR | ||
Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ PVG2011 | Serial | 1764 | ||
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Author | Anjan Dutta; Josep Llados; Umapada Pal | ||||
Title | A Bag-of-Paths Based Serialized Subgraph Matching for Symbol Spotting in Line Drawings | Type | Conference Article | ||
Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | 620-627 | |
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Abstract | In this paper we propose an error tolerant subgraph matching algorithm based on bag-of-paths for solving the problem of symbol spotting in line drawings. Bag-of-paths is a factorized representation of graphs where the factorization is done by considering all the acyclic paths between each pair of connected nodes. Similar paths within the whole collection of documents are clustered and organized in a lookup table for efficient indexing. The lookup table contains the index key of each cluster and the corresponding list of locations as a single entry. The mean path of each of the clusters serves as the index key for each table entry. The spotting method is then formulated by a spatial voting scheme to the list of locations of the paths that are decided in terms of search of similar paths that compose the query symbol. Efficient indexing of common substructures helps to reduce the computational burden of usual graph based methods. The proposed method can also be seen as a way to serialize graphs which allows to reduce the complexity of the subgraph isomorphism. We have encoded the paths in terms of both attributed strings and turning functions, and presented a comparative results between them within the symbol spotting framework. Experimentations for matching different shape silhouettes are also reported and the method has been proved to work in noisy environment also. | ||||
Address | Las Palmas de Gran Canaria. Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Berlin | Editor | Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-21256-7 | Medium | |
Area | Expedition | Conference | IbPRIA | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ DLP2011a | Serial | 1738 | ||
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