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Author | German Ros; J. Guerrero; Angel Sappa; Antonio Lopez | ||||
Title | VSLAM pose initialization via Lie groups and Lie algebras optimization | Type | Conference Article | ||
Year | 2013 | Publication | Proceedings of IEEE International Conference on Robotics and Automation | Abbreviated Journal | |
Volume ![]() |
Issue | Pages | 5740 - 5747 | ||
Keywords | SLAM | ||||
Abstract | We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm. | ||||
Address | Karlsruhe; Germany; May 2013 | ||||
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 | 1050-4729 | ISBN | 978-1-4673-5641-1 | Medium | |
Area | Expedition | Conference | ICRA | ||
Notes | ADAS; 600.054; 600.055; 600.057 | Approved | no | ||
Call Number | Admin @ si @ RGS2013a; ADAS @ adas @ | Serial | 2225 | ||
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Author | David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados | ||||
Title | Integrating Visual and Textual Cues for Query-by-String Word Spotting | Type | Conference Article | ||
Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume ![]() |
Issue | Pages | 511 - 515 | ||
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Abstract | In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances. | ||||
Address | Washington; USA; August 2013 | ||||
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 | 1520-5363 | ISBN | Medium | ||
Area | Expedition | Conference | ICDAR | ||
Notes | DAG; ADAS; 600.045; 600.055; 600.061 | Approved | no | ||
Call Number | Admin @ si @ ART2013 | Serial | 2224 | ||
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Author | Antonio Hernandez; Miguel Angel Bautista; Xavier Perez Sala; Victor Ponce; Xavier Baro; Oriol Pujol; Cecilio Angulo; Sergio Escalera | ||||
Title | BoVDW: Bag-of-Visual-and-Depth-Words for Gesture Recognition | Type | Conference Article | ||
Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
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Issue | Pages | |||
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Abstract | We present a Bag-of-Visual-and-Depth-Words (BoVDW) model for gesture recognition, an extension of the Bag-of-Visual-Words (BoVW) model, that benefits from the multimodal fusion of visual and depth features. State-of-the-art RGB and depth features, including a new proposed depth descriptor, are analysed and combined in a late fusion fashion. The method is integrated in a continuous gesture recognition pipeline, where Dynamic Time Warping (DTW) algorithm is used to perform prior segmentation of gestures. Results of the method in public data sets, within our gesture recognition pipeline, show better performance in comparison to a standard BoVW model. | ||||
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Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 1051-4651 | ISBN | 978-1-4673-2216-4 | Medium | |
Area | Expedition | Conference | ICPR | ||
Notes | HuPBA;MV | Approved | no | ||
Call Number | Admin @ si @ HBP2012 | Serial | 2122 | ||
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Author | Anjan Dutta; Jaume Gibert; Josep Llados; Horst Bunke; Umapada Pal | ||||
Title | Combination of Product Graph and Random Walk Kernel for Symbol Spotting in Graphical Documents | Type | Conference Article | ||
Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
Volume ![]() |
Issue | Pages | 1663-1666 | ||
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Abstract | This paper explores the utilization of product graph for spotting symbols on graphical documents. Product graph is intended to find the candidate subgraphs or components in the input graph containing the paths similar to the query graph. The acute angle between two edges and their length ratio are considered as the node labels. In a second step, each of the candidate subgraphs in the input graph is assigned with a distance measure computed by a random walk kernel. Actually it is the minimum of the distances of the component to all the components of the model graph. This distance measure is then used to eliminate dissimilar components. The remaining neighboring components are grouped and the grouped zone is considered as a retrieval zone of a symbol similar to the queried one. The entire method works online, i.e., it doesn't need any preprocessing step. The present paper reports the initial results of the method, which are very encouraging. | ||||
Address | Tsukuba, Japan | ||||
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 | 1051-4651 | ISBN | 978-1-4673-2216-4 | Medium | |
Area | Expedition | Conference | ICPR | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ DGL2012 | Serial | 2125 | ||
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Author | Javier Vazquez; Robert Benavente; Maria Vanrell | ||||
Title | Naming constraints constancy | Type | Conference Article | ||
Year | 2012 | Publication | 2nd Joint AVA / BMVA Meeting on Biological and Machine Vision | Abbreviated Journal | |
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Abstract | Different studies have shown that languages from industrialized cultures
share a set of 11 basic colour terms: red, green, blue, yellow, pink, purple, brown, orange, black, white, and grey (Berlin & Kay, 1969, Basic Color Terms, University of California Press)( Kay & Regier, 2003, PNAS, 100, 9085-9089). Some of these studies have also reported the best representatives or focal values of each colour (Boynton and Olson, 1990, Vision Res. 30,1311–1317), (Sturges and Whitfield, 1995, CRA, 20:6, 364–376). Some further studies have provided us with fuzzy datasets for color naming by asking human observers to rate colours in terms of membership values (Benavente -et al-, 2006, CRA. 31:1, 48–56,). Recently, a computational model based on these human ratings has been developed (Benavente -et al-, 2008, JOSA-A, 25:10, 2582-2593). This computational model follows a fuzzy approach to assign a colour name to a particular RGB value. For example, a pixel with a value (255,0,0) will be named 'red' with membership 1, while a cyan pixel with a RGB value of (0, 200, 200) will be considered to be 0.5 green and 0.5 blue. In this work, we show how this colour naming paradigm can be applied to different computer vision tasks. In particular, we report results in colour constancy (Vazquez-Corral -et al-, 2012, IEEE TIP, in press) showing that the classical constraints on either illumination or surface reflectance can be substituted by the statistical properties encoded in the colour names. [Supported by projects TIN2010-21771-C02-1, CSD2007-00018]. |
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | AV A | ||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ VBV2012 | Serial | 2131 | ||
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Author | Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco | ||||
Title | An investigation into plausible neural mechanisms related to the the CIWaM computational model for brightness induction | Type | Conference Article | ||
Year | 2012 | Publication | 2nd Joint AVA / BMVA Meeting on Biological and Machine Vision | Abbreviated Journal | |
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Issue | Pages | |||
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Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. From a purely computational perspective, we built a low-level computational model (CIWaM) of early sensory processing based on multi-resolution wavelets with the aim of replicating brightness and colour (Otazu et al., 2010, Journal of Vision, 10(12):5) induction effects. Furthermore, we successfully used the CIWaM architecture to define a computational saliency model (Murray et al, 2011, CVPR, 433-440; Vanrell et al, submitted to AVA/BMVA'12). From a biological perspective, neurophysiological evidence suggests that perceived brightness information may be explicitly represented in V1. In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (Li, 1999, Network:Comput. Neural Syst., 10, 187-212) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2-3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as visual saliency, which share with brightness induction the relevant effect of contextual influences (the ones modelled by CIWaM). In the proposed model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition taken from the computational model (CIWaM).
This model successfully accounts for well known pyschophysical effects (among them: the White's and modied White's effects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction effects) for static contexts and also for brigthness induction in dynamic contexts defined by modulating the luminance of surrounding areas. From a methodological point of view, we conclude that the results obtained by the computational model (CIWaM) are compatible with the ones obtained by the neurodynamical model proposed here. |
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | AV A | ||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ OPD2012a | Serial | 2132 | ||
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Author | Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades | ||||
Title | Text/graphic separation using a sparse representation with multi-learned dictionaries | Type | Conference Article | ||
Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
Volume ![]() |
Issue | Pages | |||
Keywords | Graphics Recognition; Layout Analysis; Document Understandin | ||||
Abstract | In this paper, we propose a new approach to extract text regions from graphical documents. In our method, we first empirically construct two sequences of learned dictionaries for the text and graphical parts respectively. Then, we compute the sparse representations of all different sizes and non-overlapped document patches in these learned dictionaries. Based on these representations, each patch can be classified into the text or graphic category by comparing its reconstruction errors. Same-sized patches in one category are then merged together to define the corresponding text or graphic layers which are combined to createfinal text/graphic layer. Finally, in a post-processing step, text regions are further filtered out by using some learned thresholds. | ||||
Address | Tsukuba | ||||
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 | ICPR | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ DTR2012a | Serial | 2135 | ||
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Author | Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades | ||||
Title | Noise suppression over bi-level graphical documents using a sparse representation | Type | Conference Article | ||
Year | 2012 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
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Address | Bordeaux | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CIFED | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ DTR2012b | Serial | 2136 | ||
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Author | Adriana Romero; Simeon Petkov; Carlo Gatta; M.Sabate; Petia Radeva | ||||
Title | Efficient automatic segmentation of vessels | Type | Conference Article | ||
Year | 2012 | Publication | 16th Conference on Medical Image Understanding and Analysis | Abbreviated Journal | |
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Address | Swansea, United Kingdom | ||||
Corporate Author | Thesis | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | MIUA | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ | Serial | 2137 | ||
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Author | Pedro Martins; Carlo Gatta; Paulo Carvalho | ||||
Title | Feature-driven Maximally Stable Extremal Regions | Type | Conference Article | ||
Year | 2012 | Publication | 7th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
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Issue | Pages | 490-497 | ||
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Area | Expedition | Conference | VISAPP | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ MGC2012 | Serial | 2139 | ||
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Author | Pedro Martins; Paulo Carvalho; Carlo Gatta | ||||
Title | Context Aware Keypoint Extraction for Robust Image Representation | Type | Conference Article | ||
Year | 2012 | Publication | 23rd British Machine Vision Conference | Abbreviated Journal | |
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Issue | Pages | 100.1 - 100.12 | ||
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Area | Expedition | Conference | BMVC | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ MCG2012a | Serial | 2140 | ||
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Author | Josep M. Gonfaus; Theo Gevers; Arjan Gijsenij; Xavier Roca; Jordi Gonzalez | ||||
Title | Edge Classification using Photo-Geo metric features | Type | Conference Article | ||
Year | 2012 | Publication | 21st International Conference on Pattern Recognition | Abbreviated Journal | |
Volume ![]() |
Issue | Pages | 1497 - 1500 | ||
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Abstract | Edges are caused by several imaging cues such as shadow, material and illumination transitions. Classification methods have been proposed which are solely based on photometric information, ignoring geometry to classify the physical nature of edges in images. In this paper, the aim is to present a novel strategy to handle both photometric and geometric information for edge classification. Photometric information is obtained through the use of quasi-invariants while geometric information is derived from the orientation and contrast of edges. Different combination frameworks are compared with a new principled approach that captures both information into the same descriptor. From large scale experiments on different datasets, it is shown that, in addition to photometric information, the geometry of edges is an important visual cue to distinguish between different edge types. It is concluded that by combining both cues the performance improves by more than 7% for shadows and highlights. | ||||
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ISSN | 1051-4651 | ISBN | 978-1-4673-2216-4 | Medium | |
Area | Expedition | Conference | ICPR | ||
Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ GGG2012b | Serial | 2142 | ||
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Author | Francesco Ciompi | ||||
Title | Multi-Class Learning for Vessel Characterization in Intravascular Ultrasound | Type | Book Whole | ||
Year | 2012 | Publication | PhD Thesis, Universitat de Barcelona-CVC | Abbreviated Journal | |
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Abstract | In this thesis we tackle the problem of automatic characterization of human coronary vessel in Intravascular Ultrasound (IVUS) image modality. The basis for the whole characterization process is machine learning applied to multi-class problems. In all the presented approaches, the Error-Correcting Output Codes (ECOC) framework is used as central element for the design of multi-class classifiers.
Two main topics are tackled in this thesis. First, the automatic detection of the vessel borders is presented. For this purpose, a novel context-aware classifier for multi-class classification of the vessel morphology is presented, namely ECOC-DRF. Based on ECOC-DRF, the lumen border and the media-adventitia border in IVUS are robustly detected by means of a novel holistic approach, achieving an error comparable with inter-observer variability and with state of the art methods. The two vessel borders define the atheroma area of the vessel. In this area, tissue characterization is required. For this purpose, we present a framework for automatic plaque characterization by processing both texture in IVUS images and spectral information in raw Radio Frequency data. Furthermore, a novel method for fusing in-vivo and in-vitro IVUS data for plaque characterization is presented, namely pSFFS. The method demonstrates to effectively fuse data generating a classifier that improves the tissue characterization in both in-vitro and in-vivo datasets. A novel method for automatic video summarization in IVUS sequences is also presented. The method aims to detect the key frames of the sequence, i.e., the frames representative of morphological changes. This novel method represents the basis for video summarization in IVUS as well as the markers for the partition of the vessel into morphological and clinically interesting events. Finally, multi-class learning based on ECOC is applied to lung tissue characterization in Computed Tomography. The novel proposed approach, based on supervised and unsupervised learning, achieves accurate tissue classification on a large and heterogeneous dataset. |
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Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Petia Radeva;Oriol Pujol | |
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ Cio2012 | Serial | 2146 | ||
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Author | Karel Paleček; David Geronimo; Frederic Lerasle | ||||
Title | Pre-attention cues for person detection | Type | Conference Article | ||
Year | 2012 | Publication | Cognitive Behavioural Systems, COST 2102 International Training School | Abbreviated Journal | |
Volume ![]() |
Issue | Pages | 225-235 | ||
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Abstract | Current state-of-the-art person detectors have been proven reliable and achieve very good detection rates. However, the performance is often far from real time, which limits their use to low resolution images only. In this paper, we deal with candidate window generation problem for person detection, i.e. we want to reduce the computational complexity of a person detector by reducing the number of regions that has to be evaluated. We base our work on Alexe’s paper [1], which introduced several pre-attention cues for generic object detection. We evaluate these cues in the context of person detection and show that their performance degrades rapidly for scenes containing multiple objects of interest such as pictures from urban environment. We extend this set by new cues, which better suits our class-specific task. The cues are designed to be simple and efficient, so that they can be used in the pre-attention phase of a more complex sliding window based person detector. | ||||
Address | Dresden, Germany | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-34583-8 | Medium | |
Area | Expedition | Conference | COST-TS | ||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ PGL2012 | Serial | 2148 | ||
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Author | Joan Arnedo-Moreno; Agata Lapedriza | ||||
Title | Visualizing key authenticity: turning your face into your public key | Type | Conference Article | ||
Year | 2010 | Publication | 6th China International Conference on Information Security and Cryptology | Abbreviated Journal | |
Volume ![]() |
Issue | Pages | 605-618 | ||
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Abstract | Biometric information has become a technology complementary to cryptography, allowing to conveniently manage cryptographic data. Two important needs are ful lled: rst of all, making such data always readily available, and additionally, making its legitimate owner easily identi able. In this work we propose a signature system which integrates face recognition biometrics with and identity-based signature scheme, so the user's face e ectively becomes his public key and system ID. Thus, other users may verify messages using photos of the claimed sender, providing a reasonable trade-o between system security and usability, as well as a much more straightforward public key authenticity and distribution process. | ||||
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Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | Inscrypt | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ ArL2010c | Serial | 2149 | ||
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