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Author | Adria Ruiz; Joost Van de Weijer; Xavier Binefa | ||||
Title | Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization | Type | Conference Article | ||
Year | 2014 | Publication | 25th British Machine Vision Conference | Abbreviated Journal | |
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Abstract | We address the problem of estimating high-level semantic labels for videos of recorded people by means of analysing their facial expressions. This problem, to which we refer as facial behavior categorization, is a weakly-supervised learning problem where we do not have access to frame-by-frame facial gesture annotations but only weak-labels at the video level are available. Therefore, the goal is to learn a set of discriminative expressions and how they determine the video weak-labels. Facial behavior categorization can be posed as a Multi-Instance-Learning (MIL) problem and we propose a novel MIL method called Regularized Multi-Concept MIL to solve it. In contrast to previous approaches applied in facial behavior analysis, RMC-MIL follows a Multi-Concept assumption which allows different facial expressions (concepts) to contribute differently to the video-label. Moreover, to handle with the high-dimensional nature of facial-descriptors, RMC-MIL uses a discriminative approach to model the concepts and structured sparsity regularization to discard non-informative features. RMC-MIL is posed as a convex-constrained optimization problem where all the parameters are jointly learned using the Projected-Quasi-Newton method. In our experiments, we use two public data-sets to show the advantages of the Regularized Multi-Concept approach and its improvement compared to existing MIL methods. RMC-MIL outperforms state-of-the-art results in the UNBC data-set for pain detection. | ||||
Address | Nottingham; UK; September 2014 | ||||
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Area | Expedition | Conference | BMVC | ||
Notes | LAMP; CIC; 600.074; 600.079 | Approved | no | ||
Call Number | Admin @ si @ RWB2014 | Serial | 2508 | ||
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Author | Marçal Rusiñol; Josep Llados | ||||
Title | Boosting the Handwritten Word Spotting Experience by Including the User in the Loop | Type | Journal Article | ||
Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 47 | Issue | 3 | Pages | 1063–1072 |
Keywords | Handwritten word spotting; Query by example; Relevance feedback; Query fusion; Multidimensional scaling | ||||
Abstract | In this paper, we study the effect of taking the user into account in a query-by-example handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and two baseline word spotting approaches both based on the bag-of-visual-words model. We finally present two alternative ways of presenting the results to the user that might be more attractive and suitable to the user's needs than the classic ranked list. | ||||
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ISSN | 0031-3203 | ISBN | Medium | ||
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Notes | DAG; 600.045; 600.061; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RuL2013 | Serial | 2343 | ||
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Author | Adriana Romero; Petia Radeva; Carlo Gatta | ||||
Title | No more meta-parameter tuning in unsupervised sparse feature learning | Type | Miscellaneous | ||
Year | 2014 | Publication | Arxiv | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | CoRR abs/1402.5766
We propose a meta-parameter free, off-the-shelf, simple and fast unsupervised feature learning algorithm, which exploits a new way of optimizing for sparsity. Experiments on STL-10 show that the method presents state-of-the-art performance and provides discriminative features that generalize well. |
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Area | Expedition | Conference | |||
Notes | MILAB; LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @ RRG2014 | Serial | 2471 | ||
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Author | Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados | ||||
Title | Classification of Administrative Document Images by Logo Identification | Type | Book Chapter | ||
Year | 2014 | Publication | Graphics Recognition. Current Trends and Challenges | Abbreviated Journal | |
Volume | 8746 | Issue | Pages | 49-58 | |
Keywords | Administrative Document Classification; Logo Recognition; Logo Spotting | ||||
Abstract | This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier’s graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Bart Lamiroy; Jean-Marc Ogier | |
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Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-662-44853-3 | Medium | |
Area | Expedition | Conference | |||
Notes | DAG; 600.056; 600.045; 605.203; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RPK2014 | Serial | 2701 | ||
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Author | Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados | ||||
Title | Spotting Graphical Symbols in Camera-Acquired Documents in Real Time | Type | Book Chapter | ||
Year | 2014 | Publication | Graphics Recognition. Current Trends and Challenges | Abbreviated Journal | |
Volume | 8746 | Issue | Pages | 3-10 | |
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Abstract | In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Bart Lamiroy; Jean-Marc Ogier | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-662-44853-3 | Medium | |
Area | Expedition | Conference | |||
Notes | DAG; 600.045; 600.055; 600.061; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RKL2014 | Serial | 2700 | ||
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Author | Christophe Rigaud; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier | ||||
Title | Color descriptor for content-based drawing retrieval | Type | Conference Article | ||
Year | 2014 | Publication | 11th IAPR International Workshop on Document Analysis and Systems | Abbreviated Journal | |
Volume | Issue | Pages | 267 - 271 | ||
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Abstract | Human detection in computer vision field is an active field of research. Extending this to human-like drawings such as the main characters in comic book stories is not trivial. Comics analysis is a very recent field of research at the intersection of graphics, texts, objects and people recognition. The detection of the main comic characters is an essential step towards a fully automatic comic book understanding. This paper presents a color-based approach for comics character retrieval using content-based drawing retrieval and color palette. | ||||
Address | Tours; Francia; April 2014 | ||||
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ISSN | ISBN | 978-1-4799-3243-6 | Medium | ||
Area | Expedition | Conference | DAS | ||
Notes | DAG; 600.056; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RKB2014 | Serial | 2479 | ||
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Author | Christophe Rigaud; Clement Guerin | ||||
Title | Localisation contextuelle des personnages de bandes dessinées | Type | Conference Article | ||
Year | 2014 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
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Abstract | Les auteurs proposent une méthode de localisation des personnages dans des cases de bandes dessinées en s'appuyant sur les caractéristiques des bulles de dialogue. L'évaluation montre un taux de localisation des personnages allant jusqu'à 65%. | ||||
Address | Nancy; Francia; March 2014 | ||||
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Area | Expedition | Conference | CIFED | ||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RiG2014 | Serial | 2481 | ||
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Author | Marçal Rusiñol; Lluis Pere de las Heras; Oriol Ramos Terrades | ||||
Title | Flowchart Recognition for Non-Textual Information Retrieval in Patent Search | Type | Journal Article | ||
Year | 2014 | Publication | Information Retrieval | Abbreviated Journal | IR |
Volume | 17 | Issue | 5-6 | Pages | 545-562 |
Keywords | Flowchart recognition; Patent documents; Text/graphics separation; Raster-to-vector conversion; Symbol recognition | ||||
Abstract | Relatively little research has been done on the topic of patent image retrieval and in general in most of the approaches the retrieval is performed in terms of a similarity measure between the query image and the images in the corpus. However, systems aimed at overcoming the semantic gap between the visual description of patent images and their conveyed concepts would be very helpful for patent professionals. In this paper we present a flowchart recognition method aimed at achieving a structured representation of flowchart images that can be further queried semantically. The proposed method was submitted to the CLEF-IP 2012 flowchart recognition task. We report the obtained results on this dataset. | ||||
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ISSN | 1386-4564 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RHR2013 | Serial | 2342 | ||
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Author | Adriana Romero; Carlo Gatta; Gustavo Camps-Valls | ||||
Title | Unsupervised Deep Feature Extraction Of Hyperspectral Images | Type | Conference Article | ||
Year | 2014 | Publication | 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Convolutional networks; deep learning; sparse learning; feature extraction; hyperspectral image classification | ||||
Abstract | This paper presents an effective unsupervised sparse feature learning algorithm to train deep convolutional networks on hyperspectral images. Deep convolutional hierarchical representations are learned and then used for pixel classification. Features in lower layers present less abstract representations of data, while higher layers represent more abstract and complex characteristics. We successfully illustrate the performance of the extracted representations in a challenging AVIRIS hyperspectral image classification problem, compared to standard dimensionality reduction methods like principal component analysis (PCA) and its kernel counterpart (kPCA). The proposed method largely outperforms the previous state-ofthe-art results on the same experimental setting. Results show that single layer networks can extract powerful discriminative features only when the receptive field accounts for neighboring pixels. Regarding the deep architecture, we can conclude that: (1) additional layers in a deep architecture significantly improve the performance w.r.t. single layer variants; (2) the max-pooling step in each layer is mandatory to achieve satisfactory results; and (3) the performance gain w.r.t. the number of layers is upper bounded, since the spatial resolution is reduced at each pooling, resulting in too spatially coarse output features. | ||||
Address | Lausanne; Switzerland; June 2014 | ||||
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Area | Expedition | Conference | WHISPERS | ||
Notes | MILAB; LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @ RGC2014 | Serial | 2513 | ||
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Author | Marçal Rusiñol; Volkmar Frinken; Dimosthenis Karatzas; Andrew Bagdanov; Josep Llados | ||||
Title | Multimodal page classification in administrative document image streams | Type | Journal Article | ||
Year | 2014 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
Volume | 17 | Issue | 4 | Pages | 331-341 |
Keywords | Digital mail room; Multimodal page classification; Visual and textual document description | ||||
Abstract | In this paper, we present a page classification application in a banking workflow. The proposed architecture represents administrative document images by merging visual and textual descriptions. The visual description is based on a hierarchical representation of the pixel intensity distribution. The textual description uses latent semantic analysis to represent document content as a mixture of topics. Several off-the-shelf classifiers and different strategies for combining visual and textual cues have been evaluated. A final step uses an n-gram model of the page stream allowing a finer-grained classification of pages. The proposed method has been tested in a real large-scale environment and we report results on a dataset of 70,000 pages. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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Series Volume | Series Issue | Edition | |||
ISSN | 1433-2833 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG; LAMP; 600.056; 600.061; 601.240; 601.223; 600.077; 600.079 | Approved | no | ||
Call Number | Admin @ si @ RFK2014 | Serial | 2523 | ||
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Author | Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier | ||||
Title | Normalisation et validation d'images de documents capturées en mobilité | Type | Conference Article | ||
Year | 2014 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
Volume | Issue | Pages | 109-124 | ||
Keywords | mobile document image acquisition; perspective correction; illumination correction; quality assessment; focus measure; OCR accuracy prediction | ||||
Abstract | Mobile document image acquisition integrates many distortions which must be corrected or detected on the device, before the document becomes unavailable or paying data transmission fees. In this paper, we propose a system to correct perspective and illumination issues, and estimate the sharpness of the image for OCR recognition. The correction step relies on fast and accurate border detection followed by illumination normalization. Its evaluation on a private dataset shows a clear improvement on OCR accuracy. The quality assessment
step relies on a combination of focus measures. Its evaluation on a public dataset shows that this simple method compares well to state of the art, learning-based methods which cannot be embedded on a mobile, and outperforms metric-based methods. |
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Address | Nancy; France; March 2014 | ||||
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Area | Expedition | Conference | CIFED | ||
Notes | DAG; 601.223; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RCO2014b | Serial | 2546 | ||
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Author | Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier | ||||
Title | Combining Focus Measure Operators to Predict OCR Accuracy in Mobile-Captured Document Images | Type | Conference Article | ||
Year | 2014 | Publication | 11th IAPR International Workshop on Document Analysis and Systems | Abbreviated Journal | |
Volume | Issue | Pages | 181 - 185 | ||
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Abstract | Mobile document image acquisition is a new trend raising serious issues in business document processing workflows. Such digitization procedure is unreliable, and integrates many distortions which must be detected as soon as possible, on the mobile, to avoid paying data transmission fees, and losing information due to the inability to re-capture later a document with temporary availability. In this context, out-of-focus blur is major issue: users have no direct control over it, and it seriously degrades OCR recognition. In this paper, we concentrate on the estimation of focus quality, to ensure a sufficient legibility of a document image for OCR processing. We propose two contributions to improve OCR accuracy prediction for mobile-captured document images. First, we present 24 focus measures, never tested on document images, which are fast to compute and require no training. Second, we show that a combination of those measures enables state-of-the art performance regarding the correlation with OCR accuracy. The resulting approach is fast, robust, and easy to implement in a mobile device. Experiments are performed on a public dataset, and precise details about image processing are given. | ||||
Address | Tours; France; April 2014 | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-4799-3243-6 | Medium | ||
Area | Expedition | Conference | DAS | ||
Notes | DAG; 601.223; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RCO2014a | Serial | 2545 | ||
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Author | P. Ricaurte; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa | ||||
Title | Performance Evaluation of Feature Point Descriptors in the Infrared Domain | Type | Conference Article | ||
Year | 2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | 1 | Issue | Pages | 545-550 | |
Keywords | Infrared Imaging; Feature Point Descriptors | ||||
Abstract | This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered. | ||||
Address | Lisboa; Portugal; January 2014 | ||||
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Area | Expedition | Conference | VISAPP | ||
Notes | ADAS; 600.055; 600.076 | Approved | no | ||
Call Number | Admin @ si @ RCA2014b | Serial | 2476 | ||
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Author | P. Ricaurte ; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa | ||||
Title | Feature Point Descriptors: Infrared and Visible Spectra | Type | Journal Article | ||
Year | 2014 | Publication | Sensors | Abbreviated Journal | SENS |
Volume | 14 | Issue | 2 | Pages | 3690-3701 |
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Abstract | This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given. | ||||
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Notes | ADAS;600.055; 600.076 | Approved | no | ||
Call Number | Admin @ si @ RCA2014a | Serial | 2474 | ||
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Author | Mohammad Rouhani; E. Boyer; Angel Sappa | ||||
Title | Non-Rigid Registration meets Surface Reconstruction | Type | Conference Article | ||
Year | 2014 | Publication | International Conference on 3D Vision | Abbreviated Journal | |
Volume | Issue | Pages | 617-624 | ||
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Abstract | Non rigid registration is an important task in computer vision with many applications in shape and motion modeling. A fundamental step of the registration is the data association between the source and the target sets. Such association proves difficult in practice, due to the discrete nature of the information and its corruption by various types of noise, e.g. outliers and missing data. In this paper we investigate the benefit of the implicit representations for the non-rigid registration of 3D point clouds. First, the target points are described with small quadratic patches that are blended through partition of unity weighting. Then, the discrete association between the source and the target can be replaced by a continuous distance field induced by the interface. By combining this distance field with a proper deformation term, the registration energy can be expressed in a linear least square form that is easy and fast to solve. This significantly eases the registration by avoiding direct association between points. Moreover, a hierarchical approach can be easily implemented by employing coarse-to-fine representations. Experimental results are provided for point clouds from multi-view data sets. The qualitative and quantitative comparisons show the outperformance and robustness of our framework. %in presence of noise and outliers. | ||||
Address | Tokyo; Japan; December 2014 | ||||
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Area | Expedition | Conference | 3DV | ||
Notes | ADAS; 600.055; 600.076 | Approved | no | ||
Call Number | Admin @ si @ RBS2014 | Serial | 2534 | ||
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