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Author | Noha Elfiky; Jordi Gonzalez; Xavier Roca | ||||
Title | Compact and Adaptive Spatial Pyramids for Scene Recognition | Type | Journal Article | ||
Year | 2012 | Publication | Image and Vision Computing | Abbreviated Journal | IMAVIS |
Volume | 30 | Issue | 8 | Pages | 492–500 |
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Abstract | Most successful approaches on scenerecognition tend to efficiently combine global image features with spatial local appearance and shape cues. On the other hand, less attention has been devoted for studying spatial texture features within scenes. Our method is based on the insight that scenes can be seen as a composition of micro-texture patterns. This paper analyzes the role of texture along with its spatial layout for scenerecognition. However, one main drawback of the resulting spatial representation is its huge dimensionality. Hence, we propose a technique that addresses this problem by presenting a compactSpatialPyramid (SP) representation. The basis of our compact representation, namely, CompactAdaptiveSpatialPyramid (CASP) consists of a two-stages compression strategy. This strategy is based on the Agglomerative Information Bottleneck (AIB) theory for (i) compressing the least informative SP features, and, (ii) automatically learning the most appropriate shape for each category. Our method exceeds the state-of-the-art results on several challenging scenerecognition data sets. | ||||
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Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ EGR2012 | Serial | 2004 | ||
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Author | Jordi Gonzalez; Thomas B. Moeslund; Liang Wang | ||||
Title | Semantic Understanding of Human Behaviors in Image Sequences: From video-surveillance to video-hermeneutics | Type | Journal Article | ||
Year | 2012 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
Volume | 116 | Issue | 3 | Pages | 305–306 |
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Abstract | Purpose: Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries.Methods: First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations.Results: The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall.Conclusions: Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed. | ||||
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ISSN | 1077-3142 | ISBN | Medium | ||
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Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ GMW2012 | Serial | 2005 | ||
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Author | Antonio Hernandez; Nadezhda Zlateva; Alexander Marinov; Miguel Reyes; Petia Radeva; Dimo Dimov; Sergio Escalera | ||||
Title | Human Limb Segmentation in Depth Maps based on Spatio-Temporal Graph Cuts Optimization | Type | Journal Article | ||
Year | 2012 | Publication | Journal of Ambient Intelligence and Smart Environments | Abbreviated Journal | JAISE |
Volume | 4 | Issue | 6 | Pages | 535-546 |
Keywords | Multi-modal vision processing; Random Forest; Graph-cuts; multi-label segmentation; human body segmentation | ||||
Abstract | We present a framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs. First, from a set of random depth features, Random Forest is used to infer a set of label probabilities for each data sample. This vector of probabilities is used as unary term in α−β swap Graph-cuts algorithm. Moreover, depth values of spatio-temporal neighboring data points are used as boundary potentials. Results on a new multi-label human depth data set show high performance in terms of segmentation overlapping of the novel methodology compared to classical approaches. | ||||
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ISSN | 1876-1364 | ISBN | Medium | ||
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Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ HZM2012a | Serial | 2006 | ||
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Author | Sophie Wuerger; Kaida Xiao; Dimitris Mylonas; Q. Huang; Dimosthenis Karatzas; Galina Paramei | ||||
Title | Blue green color categorization in mandarin english speakers | Type | Journal Article | ||
Year | 2012 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | JOSA A |
Volume | 29 | Issue | 2 | Pages | A102-A1207 |
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Abstract | Observers are faster to detect a target among a set of distracters if the targets and distracters come from different color categories. This cross-boundary advantage seems to be limited to the right visual field, which is consistent with the dominance of the left hemisphere for language processing [Gilbert et al., Proc. Natl. Acad. Sci. USA 103, 489 (2006)]. Here we study whether a similar visual field advantage is found in the color identification task in speakers of Mandarin, a language that uses a logographic system. Forty late Mandarin-English bilinguals performed a blue-green color categorization task, in a blocked design, in their first language (L1: Mandarin) or second language (L2: English). Eleven color singletons ranging from blue to green were presented for 160 ms, randomly in the left visual field (LVF) or right visual field (RVF). Color boundary and reaction times (RTs) at the color boundary were estimated in L1 and L2, for both visual fields. We found that the color boundary did not differ between the languages; RTs at the color boundary, however, were on average more than 100 ms shorter in the English compared to the Mandarin sessions, but only when the stimuli were presented in the RVF. The finding may be explained by the script nature of the two languages: Mandarin logographic characters are analyzed visuospatially in the right hemisphere, which conceivably facilitates identification of color presented to the LVF. | ||||
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ WXM2012 | Serial | 2007 | ||
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Author | Yunchao Gong; Svetlana Lazebnik; Albert Gordo; Florent Perronnin | ||||
Title | Iterative quantization: A procrustean approach to learning binary codes for Large-Scale Image Retrieval | Type | Journal Article | ||
Year | 2012 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 35 | Issue | 12 | Pages | 2916-2929 |
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Abstract | This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multi-class spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or “classemes” on the ImageNet dataset. | ||||
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ISSN | 0162-8828 | ISBN | 978-1-4577-0394-2 | Medium | |
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ GLG 2012b | Serial | 2008 | ||
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Author | Santiago Segui; Laura Igual; Jordi Vitria | ||||
Title | Bagged One Class Classifiers in the Presence of Outliers | Type | Journal Article | ||
Year | 2013 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
Volume | 27 | Issue | 5 | Pages | 1350014-1350035 |
Keywords | One-class Classifier; Ensemble Methods; Bagging and Outliers | ||||
Abstract | The problem of training classifiers only with target data arises in many applications where non-target data are too costly, difficult to obtain, or not available at all. Several one-class classification methods have been presented to solve this problem, but most of the methods are highly sensitive to the presence of outliers in the target class. Ensemble methods have therefore been proposed as a powerful way to improve the classification performance of binary/multi-class learning algorithms by introducing diversity into classifiers.
However, their application to one-class classification has been rather limited. In this paper, we present a new ensemble method based on a non-parametric weighted bagging strategy for one-class classification, to improve accuracy in the presence of outliers. While the standard bagging strategy assumes a uniform data distribution, the method we propose here estimates a probability density based on a forest structure of the data. This assumption allows the estimation of data distribution from the computation of simple univariate and bivariate kernel densities. Experiments using original and noisy versions of 20 different datasets show that bagging ensemble methods applied to different one-class classifiers outperform base one-class classification methods. Moreover, we show that, in noisy versions of the datasets, the non-parametric weighted bagging strategy we propose outperforms the classical bagging strategy in a statistically significant way. |
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Notes | OR; 600.046;MV | Approved | no | ||
Call Number | Admin @ si @ SIV2013 | Serial | 2256 | ||
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Author | Miguel Angel Bautista; Sergio Escalera; Oriol Pujol | ||||
Title | On the Design of an ECOC-Compliant Genetic Algorithm | Type | Journal Article | ||
Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 47 | Issue | 2 | Pages | 865-884 |
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Abstract | Genetic Algorithms (GA) have been previously applied to Error-Correcting Output Codes (ECOC) in state-of-the-art works in order to find a suitable coding matrix. Nevertheless, none of the presented techniques directly take into account the properties of the ECOC matrix. As a result the considered search space is unnecessarily large. In this paper, a novel Genetic strategy to optimize the ECOC coding step is presented. This novel strategy redefines the usual crossover and mutation operators in order to take into account the theoretical properties of the ECOC framework. Thus, it reduces the search space and lets the algorithm to converge faster. In addition, a novel operator that is able to enlarge the code in a smart way is introduced. The novel methodology is tested on several UCI datasets and four challenging computer vision problems. Furthermore, the analysis of the results done in terms of performance, code length and number of Support Vectors shows that the optimization process is able to find very efficient codes, in terms of the trade-off between classification performance and the number of classifiers. Finally, classification performance per dichotomizer results shows that the novel proposal is able to obtain similar or even better results while defining a more compact number of dichotomies and SVs compared to state-of-the-art approaches. | ||||
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Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ BEP2013 | Serial | 2254 | ||
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Author | Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
Title | Multispectral Piecewise Planar Stereo using Manhattan-World Assumption | Type | Journal Article | ||
Year | 2013 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 34 | Issue | 1 | Pages | 52-61 |
Keywords | Multispectral stereo rig; Dense disparity maps from multispectral stereo; Color and infrared images | ||||
Abstract | This paper proposes a new framework for extracting dense disparity maps from a multispectral stereo rig. The system is constructed with an infrared and a color camera. It is intended to explore novel multispectral stereo matching approaches that will allow further extraction of semantic information. The proposed framework consists of three stages. Firstly, an initial sparse disparity map is generated by using a cost function based on feature matching in a multiresolution scheme. Then, by looking at the color image, a set of planar hypotheses is defined to describe the surfaces on the scene. Finally, the previous stages are combined by reformulating the disparity computation as a global minimization problem. The paper has two main contributions. The first contribution combines mutual information with a shape descriptor based on gradient in a multiresolution scheme. The second contribution, which is based on the Manhattan-world assumption, extracts a dense disparity representation using the graph cut algorithm. Experimental results in outdoor scenarios are provided showing the validity of the proposed framework. | ||||
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Notes | ADAS; 600.054; 600.055; 605.203 | Approved | no | ||
Call Number | Admin @ si @ BLS2013 | Serial | 2245 | ||
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Author | Olivier Penacchio; Xavier Otazu; Laura Dempere-Marco | ||||
Title | A Neurodynamical Model of Brightness Induction in V1 | Type | Journal Article | ||
Year | 2013 | Publication | PloS ONE | Abbreviated Journal | Plos |
Volume | 8 | Issue | 5 | Pages | e64086 |
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Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway. | ||||
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ POD2013 | Serial | 2242 | ||
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Author | Naveen Onkarappa; Angel Sappa | ||||
Title | Speed and Texture: An Empirical Study on Optical-Flow Accuracy in ADAS Scenarios | Type | Journal Article | ||
Year | 2014 | Publication | IEEE Transactions on Intelligent Transportation Systems | Abbreviated Journal | TITS |
Volume | 15 | Issue | 1 | Pages | 136-147 |
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Abstract | IF: 3.064
Increasing mobility in everyday life has led to the concern for the safety of automotives and human life. Computer vision has become a valuable tool for developing driver assistance applications that target such a concern. Many such vision-based assisting systems rely on motion estimation, where optical flow has shown its potential. A variational formulation of optical flow that achieves a dense flow field involves a data term and regularization terms. Depending on the image sequence, the regularization has to appropriately be weighted for better accuracy of the flow field. Because a vehicle can be driven in different kinds of environments, roads, and speeds, optical-flow estimation has to be accurately computed in all such scenarios. In this paper, we first present the polar representation of optical flow, which is quite suitable for driving scenarios due to the possibility that it offers to independently update regularization factors in different directional components. Then, we study the influence of vehicle speed and scene texture on optical-flow accuracy. Furthermore, we analyze the relationships of these specific characteristics on a driving scenario (vehicle speed and road texture) with the regularization weights in optical flow for better accuracy. As required by the work in this paper, we have generated several synthetic sequences along with ground-truth flow fields. |
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ISSN | 1524-9050 | ISBN | Medium | ||
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Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ OnS2014a | Serial | 2386 | ||
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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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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ ABC2013 | Serial | 2313 | ||
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Author | Simone Balocco; Carlo Gatta; Francesco Ciompi; A. Wahle; Petia Radeva; S. Carlier; G. Unal; E. Sanidas; J. Mauri; X. Carillo; T. Kovarnik; C. Wang; H. Chen; T. P. Exarchos; D. I. Fotiadis; F. Destrempes; G. Cloutier; Oriol Pujol; Marina Alberti; E. G. Mendizabal-Ruiz; M. Rivera; T. Aksoy; R. W. Downe; I. A. Kakadiaris | ||||
Title | Standardized evaluation methodology and reference database for evaluating IVUS image segmentation | Type | Journal Article | ||
Year | 2014 | Publication | Computerized Medical Imaging and Graphics | Abbreviated Journal | CMIG |
Volume | 38 | Issue | 2 | Pages | 70-90 |
Keywords | IVUS (intravascular ultrasound); Evaluation framework; Algorithm comparison; Image segmentation | ||||
Abstract | This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated.
We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved. |
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Notes | MILAB; LAMP; HuPBA; 600.046; 600.063; 600.079 | Approved | no | ||
Call Number | Admin @ si @ BGC2013 | Serial | 2314 | ||
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Author | Santiago Segui; Michal Drozdzal; Fernando Vilariño; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitria | ||||
Title | Categorization and Segmentation of Intestinal Content Frames for Wireless Capsule Endoscopy | Type | Journal Article | ||
Year | 2012 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | TITB |
Volume | 16 | Issue | 6 | Pages | 1341-1352 |
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Abstract | Wireless capsule endoscopy (WCE) is a device that allows the direct visualization of gastrointestinal tract with minimal discomfort for the patient, but at the price of a large amount of time for screening. In order to reduce this time, several works have proposed to automatically remove all the frames showing intestinal content. These methods label frames as {intestinal content – clear} without discriminating between types of content (with different physiological meaning) or the portion of image covered. In addition, since the presence of intestinal content has been identified as an indicator of intestinal motility, its accurate quantification can show a potential clinical relevance. In this paper, we present a method for the robust detection and segmentation of intestinal content in WCE images, together with its further discrimination between turbid liquid and bubbles. Our proposal is based on a twofold system. First, frames presenting intestinal content are detected by a support vector machine classifier using color and textural information. Second, intestinal content frames are segmented into {turbid, bubbles, and clear} regions. We show a detailed validation using a large dataset. Our system outperforms previous methods and, for the first time, discriminates between turbid from bubbles media. | ||||
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ISSN | 1089-7771 | ISBN | Medium | ||
Area | 800 | Expedition | Conference | ||
Notes | MILAB; MV; OR;SIAI | Approved | no | ||
Call Number | Admin @ si @ SDV2012 | Serial | 2124 | ||
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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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ISSN | 1520-9210 | ISBN | Medium | ||
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Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ DSL2013; ADAS @ adas @ | Serial | 2228 | ||
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Author | Josep Llados; Marçal Rusiñol; Alicia Fornes; David Fernandez; Anjan Dutta | ||||
Title | On the Influence of Word Representations for Handwritten Word Spotting in Historical Documents | Type | Journal Article | ||
Year | 2012 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
Volume | 26 | Issue | 5 | Pages | 1263002-126027 |
Keywords | Handwriting recognition; word spotting; historical documents; feature representation; shape descriptors Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218001412630025 | ||||
Abstract | 0,624 JCR
Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely sequence alignment using DTW as a baseline reference, a bag of visual words approach as statistical model, a pseudo-structural model based on a Loci features representation, and a structural approach where words are represented by graphs. The four approaches have been tested with two collections of historical data: the George Washington database and the marriage records from the Barcelona Cathedral. We experimentally demonstrate that statistical representations generally give a better performance, however it cannot be neglected that large descriptors are difficult to be implemented in a retrieval scenario where word spotting requires the indexation of data with million word images. |
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ LRF2012 | Serial | 2128 | ||
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