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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 | ||||
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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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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 | ||||
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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 | |
Volume | 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 | |
Volume | 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 | |
Volume | Issue | Pages | |||
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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 | ||||
Corporate Author | Thesis | ||||
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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Author | Petia Radeva; Michal Drozdzal; Santiago Segui; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria | ||||
Title | Active labeling: Application to wireless endoscopy analysis | Type | Conference Article | ||
Year | 2012 | Publication | High Performance Computing and Simulation, International Conference on | Abbreviated Journal | |
Volume | Issue | Pages | 174-181 | ||
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Abstract | Today, robust learners trained in a real supervised machine learning application should count with a rich collection of positive and negative examples. Although in many applications, it is not difficult to obtain huge amount of data, labeling those data can be a very expensive process, especially when dealing with data of high variability and complexity. A good example of such cases are data from medical imaging applications where annotating anomalies like tumors, polyps, atherosclerotic plaque or informative frames in wireless endoscopy need highly trained experts. Building a representative set of training data from medical videos (e.g. Wireless Capsule Endoscopy) means that thousands of frames to be labeled by an expert. It is quite normal that data in new videos come different and thus are not represented by the training set. In this paper, we review the main approaches on active learning and illustrate how active learning can help to reduce expert effort in constructing the training sets. We show that applying active learning criteria, the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of Wireless Capsule Endoscopy video containing more than 30000 frames each one with less than 100 expert ”clicks”. | ||||
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ISSN | ISBN | 978-1-4673-2359-8 | Medium | ||
Area | Expedition | Conference | HPCS | ||
Notes | MILAB; OR;MV | Approved | no | ||
Call Number | Admin @ si @ RDS2012 | Serial | 2152 | ||
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Author | Jose Carlos Rubio; Joan Serrat; Antonio Lopez | ||||
Title | Video Co-segmentation | Type | Conference Article | ||
Year | 2012 | Publication | 11th Asian Conference on Computer Vision | Abbreviated Journal | |
Volume | 7725 | Issue | Pages | 13-24 | |
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Abstract | Segmentation of a single image is in general a highly underconstrained problem. A frequent approach to solve it is to somehow provide prior knowledge or constraints on how the objects of interest look like (in terms of their shape, size, color, location or structure). Image co-segmentation trades the need for such knowledge for something much easier to obtain, namely, additional images showing the object from other viewpoints. Now the segmentation problem is posed as one of differentiating the similar object regions in all the images from the more varying background. In this paper, for the first time, we extend this approach to video segmentation: given two or more video sequences showing the same object (or objects belonging to the same class) moving in a similar manner, we aim to outline its region in all the frames. In addition, the method works in an unsupervised manner, by learning to segment at testing time. We compare favorably with two state-of-the-art methods on video segmentation and report results on benchmark videos. | ||||
Address | Daejeon, Korea | ||||
Corporate Author | Thesis | ||||
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 | 978-3-642-37443-2 | Medium | |
Area | Expedition | Conference | ACCV | ||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ RSL2012d | Serial | 2153 | ||
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Author | Cristhian Aguilera; M.Ramos; Angel Sappa | ||||
Title | Simulated Annealing: A Novel Application of Image Processing in the Wood Area | Type | Book Chapter | ||
Year | 2012 | Publication | Simulated Annealing – Advances, Applications and Hybridizations | Abbreviated Journal | |
Volume | Issue | Pages | 91-104 | ||
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Publisher | Place of Publication | Editor | Marcos de Sales Guerra Tsuzuki | ||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | 978-953-51-0710-1 | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ ARS2012 | Serial | 2156 | ||
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Author | Monica Piñol; Angel Sappa; Ricardo Toledo | ||||
Title | MultiTable Reinforcement for Visual Object Recognition | Type | Conference Article | ||
Year | 2012 | Publication | 4th International Conference on Signal and Image Processing | Abbreviated Journal | |
Volume | 221 | Issue | Pages | 469-480 | |
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Abstract | This paper presents a bag of feature based method for visual object recognition. Our contribution is focussed on the selection of the best feature descriptor. It is implemented by using a novel multi-table reinforcement learning method that selects among five of classical descriptors (i.e., Spin, SIFT, SURF, C-SIFT and PHOW) the one that best describes each image. Experimental results and comparisons are provided showing the improvements achieved with the proposed approach. | ||||
Address | Coimbatore, India | ||||
Corporate Author | Thesis | ||||
Publisher | Springer India | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 1876-1100 | ISBN | 978-81-322-0996-6 | Medium | |
Area | Expedition | Conference | ICSIP | ||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ PST2012 | Serial | 2157 | ||
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Author | Mohammad Rouhani; Angel Sappa | ||||
Title | Non-Rigid Shape Registration: A Single Linear Least Squares Framework | Type | Conference Article | ||
Year | 2012 | Publication | 12th European Conference on Computer Vision | Abbreviated Journal | |
Volume | 7578 | Issue | Pages | 264-277 | |
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Abstract | This paper proposes a non-rigid registration formulation capturing both global and local deformations in a single framework. This formulation is based on a quadratic estimation of the registration distance together with a quadratic regularization term. Hence, the optimal transformation parameters are easily obtained by solving a liner system of equations, which guarantee a fast convergence. Experimental results with challenging 2D and 3D shapes are presented to show the validity of the proposed framework. Furthermore, comparisons with the most relevant approaches are provided. | ||||
Address | Florencia | ||||
Corporate Author | Thesis | ||||
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 | 978-3-642-33785-7 | Medium | |
Area | Expedition | Conference | ECCV | ||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ RoS2012a | Serial | 2158 | ||
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Author | Miguel Oliveira; V.Santos; Angel Sappa | ||||
Title | Short term path planning using a multiple hypothesis evaluation approach for an autonomous driving competition | Type | Conference Article | ||
Year | 2012 | Publication | IEEE 4th Workshop on Planning, Perception and Navigation for Intelligent Vehicles | Abbreviated Journal | |
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Address | Algarve; Portugal | ||||
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Area | Expedition | Conference | PPNIV | ||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ OSS2012c | Serial | 2159 | ||
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