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	Author	Suman Ghosh; Lluis Gomez; Dimosthenis Karatzas; Ernest Valveny
	Title	Efficient indexing for Query By String text retrieval			Type	Conference Article
	Year	2015	Publication	6th IAPR International Workshop on Camera Based Document Analysis and Recognition CBDAR2015	Abbreviated Journal
	Volume		Issue		Pages	1236 - 1240
	Keywords
	Abstract	This paper deals with Query By String word spotting in scene images. A hierarchical text segmentation algorithm based on text specific selective search is used to find text regions. These regions are indexed per character n-grams present in the text region. An attribute representation based on Pyramidal Histogram of Characters (PHOC) is used to compare text regions with the query text. For generation of the index a similar attribute space based Pyramidal Histogram of character n-grams is used. These attribute models are learned using linear SVMs over the Fisher Vector [1] representation of the images along with the PHOC labels of the corresponding strings.
	Address	Nancy; France; August 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CBDAR
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ GGK2015			Serial	2693
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	Author	J. Chazalon; Marçal Rusiñol; Jean-Marc Ogier
	Title	Improving Document Matching Performance by Local Descriptor Filtering			Type	Conference Article
	Year	2015	Publication	6th IAPR International Workshop on Camera Based Document Analysis and Recognition CBDAR2015	Abbreviated Journal
	Volume		Issue		Pages	1216 - 1220
	Keywords
	Abstract	In this paper we propose an effective method aimed at reducing the amount of local descriptors to be indexed in a document matching framework. In an off-line training stage, the matching between the model document and incoming images is computed retaining the local descriptors from the model that steadily produce good matches. We have evaluated this approach by using the ICDAR2015 SmartDOC dataset containing near 25 000 images from documents to be captured by a mobile device. We have tested the performance of this filtering step by using ORB and SIFT local detectors and descriptors. The results show an important gain both in quality of the final matching as well as in time and space requirements.
	Address	Nancy; France; August 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CBDAR
	Notes	DAG; 600.077; 601.223; 600.084			Approved	no
	Call Number	Admin @ si @ CRO2015a			Serial	2680
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	Author	T. Mouats; N. Aouf; Angel Sappa; Cristhian A. Aguilera-Carrasco; Ricardo Toledo
	Title	Multi-Spectral Stereo Odometry			Type	Journal Article
	Year	2015	Publication	IEEE Transactions on Intelligent Transportation Systems	Abbreviated Journal	TITS
	Volume	16	Issue	3	Pages	1210-1224
	Keywords	Egomotion estimation; feature matching; multispectral odometry (MO); optical flow; stereo odometry; thermal imagery
	Abstract	In this paper, we investigate the problem of visual odometry for ground vehicles based on the simultaneous utilization of multispectral cameras. It encompasses a stereo rig composed of an optical (visible) and thermal sensors. The novelty resides in the localization of the cameras as a stereo setup rather than two monocular cameras of different spectrums. To the best of our knowledge, this is the first time such task is attempted. Log-Gabor wavelets at different orientations and scales are used to extract interest points from both images. These are then described using a combination of frequency and spatial information within the local neighborhood. Matches between the pairs of multimodal images are computed using the cosine similarity function based on the descriptors. Pyramidal Lucas–Kanade tracker is also introduced to tackle temporal feature matching within challenging sequences of the data sets. The vehicle egomotion is computed from the triangulated 3-D points corresponding to the matched features. A windowed version of bundle adjustment incorporating Gauss–Newton optimization is utilized for motion estimation. An outlier removal scheme is also included within the framework to deal with outliers. Multispectral data sets were generated and used as test bed. They correspond to real outdoor scenarios captured using our multimodal setup. Finally, detailed results validating the proposed strategy are illustrated.
	Address
	Corporate Author				Thesis
	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; 600.055; 600.076			Approved	no
	Call Number	Admin @ si @ MAS2015a			Serial	2533
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	Author	Xavier Otazu; Olivier Penacchio; Xim Cerda-Company
	Title	Brightness and colour induction through contextual influences in V1			Type	Conference Article
	Year	2015	Publication	Scottish Vision Group 2015 SGV2015	Abbreviated Journal
	Volume	12	Issue	9	Pages	1208-2012
	Keywords
	Abstract
	Address	Carnoustie; Scotland; March 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	SGV
	Notes	NEUROBIT;			Approved	no
	Call Number	Admin @ si @ OPC2015a			Serial	2632
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	Author	Jean-Christophe Burie; J. Chazalon; M. Coustaty; S. Eskenazi; Muhammad Muzzamil Luqman; M. Mehri; Nibal Nayef; Jean-Marc Ogier; S. Prum; Marçal Rusiñol
	Title	ICDAR2015 Competition on Smartphone Document Capture and OCR (SmartDoc)			Type	Conference Article
	Year	2015	Publication	13th International Conference on Document Analysis and Recognition ICDAR2015	Abbreviated Journal
	Volume		Issue		Pages	1161 - 1165
	Keywords
	Abstract	Smartphones are enabling new ways of capture, hence arises the need for seamless and reliable acquisition and digitization of documents, in order to convert them to editable, searchable and a more human-readable format. Current stateof-the-art works lack databases and baseline benchmarks for digitizing mobile captured documents. We have organized a competition for mobile document capture and OCR in order to address this issue. The competition is structured into two independent challenges: smartphone document capture, and smartphone OCR. This report describes the datasets for both challenges along with their ground truth, details the performance evaluation protocols which we used, and presents the final results of the participating methods. In total, we received 13 submissions: 8 for challenge-I, and 5 for challenge-2.
	Address	Nancy; France; August 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG; 600.077; 601.223; 600.084			Approved	no
	Call Number	Admin @ si @ BCC2015			Serial	2681
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	Author	Dimosthenis Karatzas; Lluis Gomez; Anguelos Nicolaou; Suman Ghosh; Andrew Bagdanov; Masakazu Iwamura; J. Matas; L. Neumann; V. Ramaseshan; S. Lu ; Faisal Shafait; Seiichi Uchida; Ernest Valveny
	Title	ICDAR 2015 Competition on Robust Reading			Type	Conference Article
	Year	2015	Publication	13th International Conference on Document Analysis and Recognition ICDAR2015	Abbreviated Journal
	Volume		Issue		Pages	1156-1160
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG; 600.077; 600.084			Approved	no
	Call Number	Admin @ si @ KGN2015			Serial	2690
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	Author	Mikhail Mozerov; Joost Van de Weijer
	Title	Accurate stereo matching by two step global optimization			Type	Journal Article
	Year	2015	Publication	IEEE Transactions on Image Processing	Abbreviated Journal	TIP
	Volume	24	Issue	3	Pages	1153-1163
	Keywords
	Abstract	In stereo matching cost filtering methods and energy minimization algorithms are considered as two different techniques. Due to their global extend energy minimization methods obtain good stereo matching results. However, they tend to fail in occluded regions, in which cost filtering approaches obtain better results. In this paper we intend to combine both approaches with the aim to improve overall stereo matching results. We show that a global optimization with a fully connected model can be solved by cost fil tering methods. Based on this observation we propose to perform stereo matching as a two-step energy minimization algorithm. We consider two MRF models: a fully connected model defined on the complete set of pixels in an image and a conventional locally connected model. We solve the energy minimization problem for the fully connected model, after which the marginal function of the solution is used as the unary potential in the locally connected MRF model. Experiments on the Middlebury stereo datasets show that the proposed method achieves state-of-the-arts results.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1057-7149	ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE; LAMP; 600.079; 600.078			Approved	no
	Call Number	Admin @ si @ MoW2015a			Serial	2568
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	Author	Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Antoni Rosell; Marta Diez-Ferrer; Debora Gil
	Title	Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy			Type	Journal Article
	Year	2015	Publication	International Journal of Computer Assisted Radiology and Surgery	Abbreviated Journal	IJCAR
	Volume	10	Issue	6	Pages	935-945
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	IAM; MV; 600.075			Approved	no
	Call Number	Admin @ si @ SBS2015a			Serial	2611
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	Author	Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell; Debora Gil
	Title	Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy			Type	Conference Article
	Year	2015	Publication	6th International Conference on Information Processing in Computer-Assisted Interventions IPCAI2015	Abbreviated Journal
	Volume	10	Issue	6	Pages	935-945
	Keywords
	Abstract	PURPOSE: Lack of objective measurement of tracheal obstruction degree has a negative impact on the chosen treatment prone to lead to unnecessary repeated explorations and other scanners. Accurate computation of tracheal stenosis in videobronchoscopy would constitute a breakthrough for this noninvasive technique and a reduction in operation cost for the public health service. METHODS: Stenosis calculation is based on the comparison of the region delimited by the lumen in an obstructed frame and the region delimited by the first visible ring in a healthy frame. We propose a parametric strategy for the extraction of lumen and tracheal ring regions based on models of their geometry and appearance that guide a deformable model. To ensure a systematic applicability, we present a statistical framework to choose optimal parametric values and a strategy to choose the frames that minimize the impact of scope optical distortion. RESULTS: Our method has been tested in 40 cases covering different stenosed tracheas. Experiments report a non- clinically relevant [Formula: see text] of discrepancy in the calculated stenotic area and a computational time allowing online implementation in the operating room. CONCLUSIONS: Our methodology allows reliable measurements of airway narrowing in the operating room. To fully assess its clinical impact, a prospective clinical trial should be done.
	Address	Barcelona; Spain; June 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	IPCAI
	Notes	IAM; MV; 600.075			Approved	no
	Call Number	Admin @ si @ SBS2015b			Serial	2613
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	Author	Suman Ghosh; Ernest Valveny
	Title	Query by String word spotting based on character bi-gram indexing			Type	Conference Article
	Year	2015	Publication	13th International Conference on Document Analysis and Recognition ICDAR2015	Abbreviated Journal
	Volume		Issue		Pages	881-885
	Keywords
	Abstract	In this paper we propose a segmentation-free query by string word spotting method. Both the documents and query strings are encoded using a recently proposed word representa- tion that projects images and strings into a common atribute space based on a pyramidal histogram of characters(PHOC). These attribute models are learned using linear SVMs over the Fisher Vector representation of the images along with the PHOC labels of the corresponding strings. In order to search through the whole page, document regions are indexed per character bi- gram using a similar attribute representation. On top of that, we propose an integral image representation of the document using a simplified version of the attribute model for efficient computation. Finally we introduce a re-ranking step in order to boost retrieval performance. We show state-of-the-art results for segmentation-free query by string word spotting in single-writer and multi-writer standard datasets
	Address	Nancy; France; August 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ GhV2015a			Serial	2715
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	Author	Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
	Title	Combining Local and Global Learners in the Pairwise Multiclass Classification			Type	Journal Article
	Year	2015	Publication	Pattern Analysis and Applications	Abbreviated Journal	PAA
	Volume	18	Issue	4	Pages	845-860
	Keywords	Multiclass classification; Pairwise approach; One-versus-one
	Abstract	Pairwise classification is a well-known class binarization technique that converts a multiclass problem into a number of two-class problems, one problem for each pair of classes. However, in the pairwise technique, nuisance votes of many irrelevant classifiers may result in a wrong class prediction. To overcome this problem, a simple, but efficient method is proposed and evaluated in this paper. The proposed method is based on excluding some classes and focusing on the most probable classes in the neighborhood space, named Local Crossing Off (LCO). This procedure is performed by employing a modified version of standard K-nearest neighbor and large margin nearest neighbor algorithms. The LCO method takes advantage of nearest neighbor classification algorithm because of its local learning behavior as well as the global behavior of powerful binary classifiers to discriminate between two classes. Combining these two properties in the proposed LCO technique will avoid the weaknesses of each method and will increase the efficiency of the whole classification system. On several benchmark datasets of varying size and difficulty, we found that the LCO approach leads to significant improvements using different base learners. The experimental results show that the proposed technique not only achieves better classification accuracy in comparison to other standard approaches, but also is computationally more efficient for tackling classification problems which have a relatively large number of target classes.
	Address
	Corporate Author				Thesis
	Publisher	Springer London	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1433-7541	ISBN		Medium
	Area		Expedition		Conference
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ BGE2014			Serial	2441
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	Author	Pau Riba; Josep Llados; Alicia Fornes
	Title	Handwritten Word Spotting by Inexact Matching of Grapheme Graphs			Type	Conference Article
	Year	2015	Publication	13th International Conference on Document Analysis and Recognition ICDAR2015	Abbreviated Journal
	Volume		Issue		Pages	781 - 785
	Keywords
	Abstract	This paper presents a graph-based word spotting for handwritten documents. Contrary to most word spotting techniques, which use statistical representations, we propose a structural representation suitable to be robust to the inherent deformations of handwriting. Attributed graphs are constructed using a part-based approach. Graphemes extracted from shape convexities are used as stable units of handwriting, and are associated to graph nodes. Then, spatial relations between them determine graph edges. Spotting is defined in terms of an error-tolerant graph matching using bipartite-graph matching algorithm. To make the method usable in large datasets, a graph indexing approach that makes use of binary embeddings is used as preprocessing. Historical documents are used as experimental framework. The approach is comparable to statistical ones in terms of time and memory requirements, especially when dealing with large document collections.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG; 600.077; 600.061; 602.006			Approved	no
	Call Number	Admin @ si @ RLF2015b			Serial	2642
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	Author	Lluis Pere de las Heras; Oriol Ramos Terrades; Josep Llados
	Title	Attributed Graph Grammar for floor plan analysis			Type	Conference Article
	Year	2015	Publication	13th International Conference on Document Analysis and Recognition ICDAR2015	Abbreviated Journal
	Volume		Issue		Pages	726 - 730
	Keywords
	Abstract	In this paper, we propose the use of an Attributed Graph Grammar as unique framework to model and recognize the structure of floor plans. This grammar represents a building as a hierarchical composition of structurally and semantically related elements, where common representations are learned stochastically from annotated data. Given an input image, the parsing consists on constructing that graph representation that better agrees with the probabilistic model defined by the grammar. The proposed method provides several advantages with respect to the traditional floor plan analysis techniques. It uses an unsupervised statistical approach for detecting walls that adapts to different graphical notations and relaxes strong structural assumptions such are straightness and orthogonality. Moreover, the independence between the knowledge model and the parsing implementation allows the method to learn automatically different building configurations and thus, to cope the existing variability. These advantages are clearly demonstrated by comparing it with the most recent floor plan interpretation techniques on 4 datasets of real floor plans with different notations.
	Address	Nancy; France; August 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG; 600.077; 600.061			Approved	no
	Call Number	Admin @ si @ HRL2015b			Serial	2727
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	Author	Lluis Pere de las Heras; Oriol Ramos Terrades; Josep Llados; David Fernandez; Cristina Cañero
	Title	Use case visual Bag-of-Words techniques for camera based identity document classification			Type	Conference Article
	Year	2015	Publication	13th International Conference on Document Analysis and Recognition ICDAR2015	Abbreviated Journal
	Volume		Issue		Pages	721 - 725
	Keywords
	Abstract	Nowadays, automatic identity document recognition, including passport and driving license recognition, is at the core of many applications within the administrative and service sectors, such as police, hospitality, car renting, etc. In former years, the document information was manually extracted whereas today this data is recognized automatically from images obtained by flat-bed scanners. Yet, since these scanners tend to be expensive and voluminous, companies in the sector have recently turned their attention to cheaper, small and yet computationally powerful scanners: the mobile devices. The document identity recognition from mobile images enclose several new difficulties w.r.t traditional scanned images, such as the loss of a controlled background, perspective, blurring, etc. In this paper we present a real application for identity document classification of images taken from mobile devices. This classification process is of extreme importance since a prior knowledge of the document type and origin strongly facilitates the subsequent information extraction. The proposed method is based on a traditional Bagof-Words in which we have taken into consideration several key aspects to enhance recognition rate. The method performance has been studied on three datasets containing more than 2000 images from 129 different document classes.
	Address	Nancy; France; August 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG; 600.077; 600.061;			Approved	no
	Call Number	Admin @ si @ HRL2015a			Serial	2726
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	Author	Anguelos Nicolaou; Andrew Bagdanov; Marcus Liwicki; Dimosthenis Karatzas
	Title	Sparse Radial Sampling LBP for Writer Identification			Type	Conference Article
	Year	2015	Publication	13th International Conference on Document Analysis and Recognition ICDAR2015	Abbreviated Journal
	Volume		Issue		Pages	716-720
	Keywords
	Abstract	In this paper we present the use of Sparse Radial Sampling Local Binary Patterns, a variant of Local Binary Patterns (LBP) for text-as-texture classification. By adapting and extending the standard LBP operator to the particularities of text we get a generic text-as-texture classification scheme and apply it to writer identification. In experiments on CVL and ICDAR 2013 datasets, the proposed feature-set demonstrates State-Of-the-Art (SOA) performance. Among the SOA, the proposed method is the only one that is based on dense extraction of a single local feature descriptor. This makes it fast and applicable at the earliest stages in a DIA pipeline without the need for segmentation, binarization, or extraction of multiple features.
	Address	Nancy; France; August 2015
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ NBL2015			Serial	2692
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