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| Author | Ferran Diego; Joan Serrat; Antonio Lopez | ||||
| Title | Joint spatio-temporal alignment of sequences | Type | Journal Article | ||
| Year | 2013 | Publication | IEEE Transactions on Multimedia | Abbreviated Journal | TMM |
| Volume | 15 | Issue | 6 | Pages  |
1377-1387 |
| Keywords | video alignment | ||||
| Abstract | Video alignment is important in different areas of computer vision such as wide baseline matching, action recognition, change detection, video copy detection and frame dropping prevention. Current video alignment methods usually deal with a relatively simple case of fixed or rigidly attached cameras or simultaneous acquisition. Therefore, in this paper we propose a joint video alignment for bringing two video sequences into a spatio-temporal alignment. Specifically, the novelty of the paper is to formulate the video alignment to fold the spatial and temporal alignment into a single alignment framework. This simultaneously satisfies a frame-correspondence and frame-alignment similarity; exploiting the knowledge among neighbor frames by a standard pairwise Markov random field (MRF). This new formulation is able to handle the alignment of sequences recorded at different times by independent moving cameras that follows a similar trajectory, and also generalizes the particular cases that of fixed geometric transformation and/or linear temporal mapping. We conduct experiments on different scenarios such as sequences recorded simultaneously or by moving cameras to validate the robustness of the proposed approach. The proposed method provides the highest video alignment accuracy compared to the state-of-the-art methods on sequences recorded from vehicles driving along the same track at different times. | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-9210 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ DSL2013; ADAS @ adas @ | Serial | 2228 | ||
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| Author | M. Visani; V.C.Kieu; Alicia Fornes; N.Journet | ||||
| Title | The ICDAR 2013 Music Scores Competition: Staff Removal | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages |
1439-1443 | ||
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| Abstract | The first competition on music scores that was organized at ICDAR in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario: old music scores. For this purpose, we have generated a new set of images using two kinds of degradations: local noise and 3D distortions. This paper describes the dataset, distortion methods, evaluation metrics, the participant's methods and the obtained results. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.045; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ VKF2013 | Serial | 2338 | ||
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| Author | Dimosthenis Karatzas; Faisal Shafait; Seiichi Uchida; Masakazu Iwamura; Lluis Gomez; Sergi Robles; Joan Mas; David Fernandez; Jon Almazan; Lluis Pere de las Heras | ||||
| Title | ICDAR 2013 Robust Reading Competition | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages |
1484-1493 | ||
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| Abstract | This report presents the final results of the ICDAR 2013 Robust Reading Competition. The competition is structured in three Challenges addressing text extraction in different application domains, namely born-digital images, real scene images and real-scene videos. The Challenges are organised around specific tasks covering text localisation, text segmentation and word recognition. The competition took place in the first quarter of 2013, and received a total of 42 submissions over the different tasks offered. This report describes the datasets and ground truth specification, details the performance evaluation protocols used and presents the final results along with a brief summary of the participating methods. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.056 | Approved | no | ||
| Call Number | Admin @ si @ KSU2013 | Serial | 2318 | ||
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| Author | Hamdi Dibeklioglu; Albert Ali Salah; Theo Gevers | ||||
| Title | Like Father, Like Son: Facial Expression Dynamics for Kinship Verification | Type | Conference Article | ||
| Year | 2013 | Publication | 15th IEEE International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages |
1497-1504 | ||
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| Abstract | Kinship verification from facial appearance is a difficult problem. This paper explores the possibility of employing facial expression dynamics in this problem. By using features that describe facial dynamics and spatio-temporal appearance over smile expressions, we show that it is possible to improve the state of the art in this problem, and verify that it is indeed possible to recognize kinship by resemblance of facial expressions. The proposed method is tested on different kin relationships. On the average, 72.89% verification accuracy is achieved on spontaneous smiles. | ||||
| Address | Sydney | ||||
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| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICCV | ||
| Notes | ALTRES;ISE | Approved | no | ||
| Call Number | Admin @ si @ DSG2013 | Serial | 2366 | ||
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| Author | Veronica Romero; Alicia Fornes; Nicolas Serrano; Joan Andreu Sanchez; A.H. Toselli; Volkmar Frinken; E. Vidal; Josep Llados | ||||
| Title | The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition | Type | Journal Article | ||
| Year | 2013 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 46 | Issue | 6 | Pages |
1658-1669 |
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| Abstract | Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demography studies and genealogical research. Automatic processing of historical documents, however, has mostly been focused on single works of literature and less on social records, which tend to have a distinct layout, structure, and vocabulary. Such information is usually collected by expert demographers that devote a lot of time to manually transcribe them. This paper presents a new database, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records. Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. Books from this collection are handwritten and span nearly half a millennium until the beginning of the 20th century. In addition, a study is presented about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database. Baseline results are reported for reference in future studies. | ||||
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| Publisher | Elsevier Science Inc. New York, NY, USA | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0031-3203 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.045; 602.006; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ RFS2013 | Serial | 2298 | ||
| Permanent link to this record | |||||
| Author | Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title | Automatic non-rigid temporal alignment of IVUS sequences: method and quantitative validation | Type | Journal Article | ||
| Year | 2013 | Publication | Ultrasound in Medicine and Biology | Abbreviated Journal | UMB |
| Volume | 39 | Issue | 9 | Pages |
1698-712 |
| Keywords | Intravascular ultrasound; Dynamic time warping; Non-rigid alignment; Sequence matching; Partial overlapping strategy | ||||
| Abstract | Clinical studies on atherosclerosis regression/progression performed by intravascular ultrasound analysis would benefit from accurate alignment of sequences of the same patient before and after clinical interventions and at follow-up. In this article, a methodology for automatic alignment of intravascular ultrasound sequences based on the dynamic time warping technique is proposed. The non-rigid alignment is adapted to the specific task by applying it to multidimensional signals describing the morphologic content of the vessel. Moreover, dynamic time warping is embedded into a framework comprising a strategy to address partial overlapping between acquisitions and a term that regularizes non-physiologic temporal compression/expansion of the sequences. Extensive validation is performed on both synthetic and in vivo data. The proposed method reaches alignment errors of approximately 0.43 mm for pairs of sequences acquired during the same intervention phase and 0.77 mm for pairs of sequences acquired at successive intervention stages. | ||||
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| Area | Expedition | Conference | |||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ ABC2013 | Serial | 2313 | ||
| Permanent link to this record | |||||
| Author | Albert Gordo; Florent Perronnin; Ernest Valveny | ||||
| Title | Large-scale document image retrieval and classification with runlength histograms and binary embeddings | Type | Journal Article | ||
| Year | 2013 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 46 | Issue | 7 | Pages |
1898-1905 |
| Keywords | visual document descriptor; compression; large-scale; retrieval; classification | ||||
| Abstract | We present a new document image descriptor based on multi-scale runlength
histograms. This descriptor does not rely on layout analysis and can be computed efficiently. We show how this descriptor can achieve state-of-theart results on two very different public datasets in classification and retrieval tasks. Moreover, we show how we can compress and binarize these descriptors to make them suitable for large-scale applications. We can achieve state-ofthe- art results in classification using binary descriptors of as few as 16 to 64 bits. |
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0031-3203 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.042; 600.045; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ GPV2013 | Serial | 2306 | ||
| Permanent link to this record | |||||
| Author | Mikhail Mozerov | ||||
| Title | Constrained Optical Flow Estimation as a Matching Problem | Type | Journal Article | ||
| Year | 2013 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
| Volume | 22 | Issue | 5 | Pages |
2044-2055 |
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| Abstract | In general, discretization in the motion vector domain yields an intractable number of labels. In this paper we propose an approach that can reduce general optical flow to the constrained matching problem by pre-estimating a 2D disparity labeling map of the desired discrete motion vector function. One of the goals of the proposed paper is estimating coarse distribution of motion vectors and then utilizing this distribution as global constraints for discrete optical flow estimation. This pre-estimation is done with a simple frame-to-frame correlation technique also known as the digital symmetric-phase-only-filter (SPOF). We discover a strong correlation between the output of the SPOF and the motion vector distribution of the related optical flow. The two step matching paradigm for optical flow estimation is applied: pixel accuracy (integer flow), and subpixel accuracy estimation. The matching problem is solved by global optimization. Experiments on the Middlebury optical flow datasets confirm our intuitive assumptions about strong correlation between motion vector distribution of optical flow and maximal peaks of SPOF outputs. The overall performance of the proposed method is promising and achieves state-of-the-art results on the Middlebury benchmark. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1057-7149 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ Moz2013 | Serial | 2191 | ||
| Permanent link to this record | |||||
| Author | Rahat Khan; Joost Van de Weijer; Dimosthenis Karatzas; Damien Muselet | ||||
| Title | Towards multispectral data acquisition with hand-held devices | Type | Conference Article | ||
| Year | 2013 | Publication | 20th IEEE International Conference on Image Processing | Abbreviated Journal | |
| Volume | Issue | Pages |
2053 - 2057 | ||
| Keywords | Multispectral; mobile devices; color measurements | ||||
| Abstract | We propose a method to acquire multispectral data with handheld devices with front-mounted RGB cameras. We propose to use the display of the device as an illuminant while the camera captures images illuminated by the red, green and
blue primaries of the display. Three illuminants and three response functions of the camera lead to nine response values which are used for reflectance estimation. Results are promising and show that the accuracy of the spectral reconstruction improves in the range from 30-40% over the spectral reconstruction based on a single illuminant. Furthermore, we propose to compute sensor-illuminant aware linear basis by discarding the part of the reflectances that falls in the sensorilluminant null-space. We show experimentally that optimizing reflectance estimation on these new basis functions decreases the RMSE significantly over basis functions that are independent to sensor-illuminant. We conclude that, multispectral data acquisition is potentially possible with consumer hand-held devices such as tablets, mobiles, and laptops, opening up applications which are currently considered to be unrealistic. |
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| Address | Melbourne; Australia; September 2013 | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICIP | ||
| Notes | CIC; DAG; 600.048 | Approved | no | ||
| Call Number | Admin @ si @ KWK2013b | Serial | 2265 | ||
| Permanent link to this record | |||||
| Author | Gemma Roig; Xavier Boix; R. de Nijs; Sebastian Ramos; K. Kühnlenz; Luc Van Gool | ||||
| Title | Active MAP Inference in CRFs for Efficient Semantic Segmentation | Type | Conference Article | ||
| Year | 2013 | Publication | 15th IEEE International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages |
2312 - 2319 | ||
| Keywords | Semantic Segmentation | ||||
| Abstract | Most MAP inference algorithms for CRFs optimize an energy function knowing all the potentials. In this paper, we focus on CRFs where the computational cost of instantiating the potentials is orders of magnitude higher than MAP inference. This is often the case in semantic image segmentation, where most potentials are instantiated by slow classifiers fed with costly features. We introduce Active MAP inference 1) to on-the-fly select a subset of potentials to be instantiated in the energy function, leaving the rest of the parameters of the potentials unknown, and 2) to estimate the MAP labeling from such incomplete energy function. Results for semantic segmentation benchmarks, namely PASCAL VOC 2010 [5] and MSRC-21 [19], show that Active MAP inference achieves similar levels of accuracy but with major efficiency gains. | ||||
| Address | Sydney; Australia; December 2013 | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1550-5499 | ISBN | Medium | ||
| Area | Expedition | Conference | ICCV | ||
| Notes | ADAS; 600.057 | Approved | no | ||
| Call Number | ADAS @ adas @ RBN2013 | Serial | 2377 | ||
| Permanent link to this record | |||||
| Author | Javier Marin; David Vazquez; Antonio Lopez; Jaume Amores; Bastian Leibe | ||||
| Title | Random Forests of Local Experts for Pedestrian Detection | Type | Conference Article | ||
| Year | 2013 | Publication | 15th IEEE International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages |
2592 - 2599 | ||
| Keywords | ADAS; Random Forest; Pedestrian Detection | ||||
| Abstract | Pedestrian detection is one of the most challenging tasks in computer vision, and has received a lot of attention in the last years. Recently, some authors have shown the advantages of using combinations of part/patch-based detectors in order to cope with the large variability of poses and the existence of partial occlusions. In this paper, we propose a pedestrian detection method that efficiently combines multiple local experts by means of a Random Forest ensemble. The proposed method works with rich block-based representations such as HOG and LBP, in such a way that the same features are reused by the multiple local experts, so that no extra computational cost is needed with respect to a holistic method. Furthermore, we demonstrate how to integrate the proposed approach with a cascaded architecture in order to achieve not only high accuracy but also an acceptable efficiency. In particular, the resulting detector operates at five frames per second using a laptop machine. We tested the proposed method with well-known challenging datasets such as Caltech, ETH, Daimler, and INRIA. The method proposed in this work consistently ranks among the top performers in all the datasets, being either the best method or having a small difference with the best one. | ||||
| Address | Sydney; Australia; December 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | IEEE | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1550-5499 | ISBN | Medium | ||
| Area | Expedition | Conference | ICCV | ||
| Notes | ADAS; 600.057; 600.054 | Approved | no | ||
| Call Number | ADAS @ adas @ MVL2013 | Serial | 2333 | ||
| Permanent link to this record | |||||
| Author | Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga | ||||
| Title | Low-level SpatioChromatic Grouping for Saliency Estimation | Type | Journal Article | ||
| Year | 2013 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 35 | Issue | 11 | Pages |
2810-2816 |
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| Abstract | We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics. | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0162-8828 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | CIC; 600.051; 600.052; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ MVO2013 | Serial | 2289 | ||
| Permanent link to this record | |||||
| Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
| Title | A Genetic-based Subspace Analysis Method for Improving Error-Correcting Output Coding | Type | Journal Article | ||
| Year | 2013 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 46 | Issue | 10 | Pages |
2830-2839 |
| Keywords | Error Correcting Output Codes; Evolutionary computation; Multiclass classification; Feature subspace; Ensemble classification | ||||
| Abstract | Two key factors affecting the performance of Error Correcting Output Codes (ECOC) in multiclass classification problems are the independence of binary classifiers and the problem-dependent coding design. In this paper, we propose an evolutionary algorithm-based approach to the design of an application-dependent codematrix in the ECOC framework. The central idea of this work is to design a three-dimensional codematrix, where the third dimension is the feature space of the problem domain. In order to do that, we consider the feature space in the design process of the codematrix with the aim of improving the independence and accuracy of binary classifiers. The proposed method takes advantage of some basic concepts of ensemble classification, such as diversity of classifiers, and also benefits from the evolutionary approach for optimizing the three-dimensional codematrix, taking into account the problem domain. We provide a set of experimental results using a set of benchmark datasets from the UCI Machine Learning Repository, as well as two real multiclass Computer Vision problems. Both sets of experiments are conducted using two different base learners: Neural Networks and Decision Trees. The results show that the proposed method increases the classification accuracy in comparison with the state-of-the-art ECOC coding techniques. | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0031-3203 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ BGE2013a | Serial | 2247 | ||
| Permanent link to this record | |||||
| Author | Ivo Everts; Jan van Gemert; Theo Gevers | ||||
| Title | Evaluation of Color STIPs for Human Action Recognition | Type | Conference Article | ||
| Year | 2013 | Publication | IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages |
2850-2857 | ||
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| Abstract | This paper is concerned with recognizing realistic human actions in videos based on spatio-temporal interest points (STIPs). Existing STIP-based action recognition approaches operate on intensity representations of the image data. Because of this, these approaches are sensitive to disturbing photometric phenomena such as highlights and shadows. Moreover, valuable information is neglected by discarding chromaticity from the photometric representation. These issues are addressed by Color STIPs. Color STIPs are multi-channel reformulations of existing intensity-based STIP detectors and descriptors, for which we consider a number of chromatic representations derived from the opponent color space. This enhanced modeling of appearance improves the quality of subsequent STIP detection and description. Color STIPs are shown to substantially outperform their intensity-based counterparts on the challenging UCF~sports, UCF11 and UCF50 action recognition benchmarks. Moreover, the results show that color STIPs are currently the single best low-level feature choice for STIP-based approaches to human action recognition. | ||||
| Address | Portland; oregon; June 2013 | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1063-6919 | ISBN | Medium | ||
| Area | Expedition | Conference | CVPR | ||
| Notes | ALTRES;ISE | Approved | no | ||
| Call Number | Admin @ si @ EGG2013 | Serial | 2364 | ||
| Permanent link to this record | |||||
| Author | Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat | ||||
| Title | Discriminative Color Descriptors | Type | Conference Article | ||
| Year | 2013 | Publication | IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages |
2866 - 2873 | ||
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| Abstract | Color description is a challenging task because of large variations in RGB values which occur due to scene accidental events, such as shadows, shading, specularities, illuminant color changes, and changes in viewing geometry. Traditionally, this challenge has been addressed by capturing the variations in physics-based models, and deriving invariants for the undesired variations. The drawback of this approach is that sets of distinguishable colors in the original color space are mapped to the same value in the photometric invariant space. This results in a drop of discriminative power of the color description. In this paper we take an information theoretic approach to color description. We cluster color values together based on their discriminative power in a classification problem. The clustering has the explicit objective to minimize the drop of mutual information of the final representation. We show that such a color description automatically learns a certain degree of photometric invariance. We also show that a universal color representation, which is based on other data sets than the one at hand, can obtain competing performance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape description these color descriptors obtain excellent results on four challenging datasets, namely, PASCAL VOC 2007, Flowers-102, Stanford dogs-120 and Birds-200. | ||||
| Address | Portland; Oregon; June 2013 | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1063-6919 | ISBN | Medium | ||
| Area | Expedition | Conference | CVPR | ||
| Notes | CIC; 600.048 | Approved | no | ||
| Call Number | Admin @ si @ KWK2013a | Serial | 2262 | ||
| Permanent link to this record | |||||