Records |
Author |
Francesco Ciompi; A. Palaioroutas; M. Loeve; Oriol Pujol; Petia Radeva; H. Tiddens; M. de Bruijne |
Title |
Lung Tissue Classification in Severe Advanced Cystic Fibrosis from CT Scans |
Type |
Conference Article |
Year |
2011 |
Publication |
In MICCAI 2011 4th International Workshop on Pulmonary Image Analysis |
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Toronto, Canada |
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PIA |
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MILAB;HuPBA |
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no |
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Admin @ si @ CPL2011 |
Serial |
1798 |
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Author |
Simone Balocco; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva |
Title |
Plaque Type, Plaque Burden and Wall Shear Stress Relation in Coronary Arteries Assessed by X-ray Angiography and Intravascular Ultrasound: a Qualitative Study |
Type |
Conference Article |
Year |
2011 |
Publication |
14th International Symposium on Applied Sciences in Biomedical and Communication Technologies |
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In this paper, we present a complete framework that automatically provides fluid-dynamic and plaque analysis from IVUS and Angiographic sequences. Such framework is used to analyze, in three coronary arteries, the relation between wall shear stress with type and amount of plaque. Preliminary qualitative results show an inverse relation between the wall shear stress and the plaque burden, which is confirmed by the fact that the plaque growth is higher on the wall having concave curvature. Regarding the plaque type it was observed that regions having low shear stress are predominantly fibro-lipidic while the heavy calcifications are in general located in areas of the vessel having high WSS. |
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978-1-4503-0913-4 |
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ISABEL |
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MILAB |
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no |
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Admin @ si @ BGC2011b |
Serial |
1799 |
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Author |
Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva |
Title |
Traffic-Sign Recognition Systems |
Type |
Book Whole |
Year |
2011 |
Publication |
SpringerBriefs in Computer Science |
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5-13 |
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Springer London |
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978-1-4471-2244-9 |
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MILAB; OR;HuPBA;MV |
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no |
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Admin @ si @ EBP2011 |
Serial |
1801 |
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Author |
E. Serradell; Adriana Romero; R. Leta; Carlo Gatta; Francesc Moreno-Noguer |
Title |
Simultaneous Correspondence and Non-Rigid 3D Reconstruction of the Coronary Tree from Single X-Ray Images |
Type |
Conference Article |
Year |
2011 |
Publication |
13th IEEE International Conference on Computer Vision |
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850-857 |
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Barcelona |
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ICCV |
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MILAB |
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no |
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Admin @ si @ SRL2011 |
Serial |
1803 |
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Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
Title |
Near Convex Region Adjacency Graph and Approximate Neighborhood String Matching for Symbol Spotting in Graphical Documents |
Type |
Conference Article |
Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
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1078-1082 |
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This paper deals with a subgraph matching problem in Region Adjacency Graph (RAG) applied to symbol spotting in graphical documents. RAG is a very important, efficient and natural way of representing graphical information with a graph but this is limited to cases where the information is well defined with perfectly delineated regions. What if the information we are interested in is not confined within well defined regions? This paper addresses this particular problem and solves it by defining near convex grouping of oriented line segments which results in near convex regions. Pure convexity imposes hard constraints and can not handle all the cases efficiently. Hence to solve this problem we have defined a new type of convexity of regions, which allows convex regions to have concavity to some extend. We call this kind of regions Near Convex Regions (NCRs). These NCRs are then used to create the Near Convex Region Adjacency Graph (NCRAG) and with this representation we have formulated the problem of symbol spotting in graphical documents as a subgraph matching problem. For subgraph matching we have used the Approximate Edit Distance Algorithm (AEDA) on the neighborhood string, which starts working after finding a key node in the input or target graph and iteratively identifies similar nodes of the query graph in the neighborhood of the key node. The experiments are performed on artificial, real and distorted datasets. |
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Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
Notes |
DAG; 600.045; 600.056; 600.061; 601.152 |
Approved |
no |
Call Number |
Admin @ si @ DLB2013a |
Serial |
2358 |
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Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
Title |
A Product graph based method for dual subgraph matching applied to symbol spotting |
Type |
Conference Article |
Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
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Product graph has been shown to be an efficient way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. This paper focuses on the two major limitations of the previous version of product graph: (1) Spurious nodes and edges in the graph representation and (2) Inefficient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual graph representation on the original graph representing the graphical information and the product graph is computed between the dual graphs of the query graphs and the input graph.
The dual graph with redundant edges is helpful for efficient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates similar path information of two graphs and exponentiating the adjacency matrix finds similar paths of greater lengths. Nodes joining similar paths between two graphs are found by combining different exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging. |
Address |
Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG |
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no |
Call Number |
Admin @ si @ DLB2013b |
Serial |
2359 |
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Author |
Nataliya Shapovalova; Carles Fernandez; Xavier Roca; Jordi Gonzalez |
Title |
Semantics of Human Behavior in Image Sequences |
Type |
Book Chapter |
Year |
2011 |
Publication |
Computer Analysis of Human Behavior |
Abbreviated Journal |
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Issue |
7 |
Pages |
151-182 |
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Abstract |
Human behavior is contextualized and understanding the scene of an action is crucial for giving proper semantics to behavior. In this chapter we present a novel approach for scene understanding. The emphasis of this work is on the particular case of Human Event Understanding. We introduce a new taxonomy to organize the different semantic levels of the Human Event Understanding framework proposed. Such a framework particularly contributes to the scene understanding domain by (i) extracting behavioral patterns from the integrative analysis of spatial, temporal, and contextual evidence and (ii) integrative analysis of bottom-up and top-down approaches in Human Event Understanding. We will explore how the information about interactions between humans and their environment influences the performance of activity recognition, and how this can be extrapolated to the temporal domain in order to extract higher inferences from human events observed in sequences of images. |
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Publisher |
Springer London |
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Editor |
Albert Ali Salah; |
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978-0-85729-993-2 |
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ISE |
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no |
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Admin @ si @ SFR2011 |
Serial |
1810 |
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Author |
Bhaskar Chakraborty; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez; Xavier Roca |
Title |
A Selective Spatio-Temporal Interest Point Detector for Human Action Recognition in Complex Scenes |
Type |
Conference Article |
Year |
2011 |
Publication |
13th IEEE International Conference on Computer Vision |
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Pages |
1776-1783 |
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Abstract |
Recent progress in the field of human action recognition points towards the use of Spatio-Temporal Interest Points (STIPs) for local descriptor-based recognition strategies. In this paper we present a new approach for STIP detection by applying surround suppression combined with local and temporal constraints. Our method is significantly different from existing STIP detectors and improves the performance by detecting more repeatable, stable and distinctive STIPs for human actors, while suppressing unwanted background STIPs. For action representation we use a bag-of-visual words (BoV) model of local N-jet features to build a vocabulary of visual-words. To this end, we introduce a novel vocabulary building strategy by combining spatial pyramid and vocabulary compression techniques, resulting in improved performance and efficiency. Action class specific Support Vector Machine (SVM) classifiers are trained for categorization of human actions. A comprehensive set of experiments on existing benchmark datasets, and more challenging datasets of complex scenes, validate our approach and show state-of-the-art performance. |
Address |
Barcelona |
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Edition |
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ISSN |
1550-5499 |
ISBN |
978-1-4577-1101-5 |
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Conference |
ICCV |
Notes |
ISE |
Approved |
no |
Call Number |
Admin @ si @ CHM2011 |
Serial |
1811 |
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Author |
Wenjuan Gong; Jürgen Brauer; Michael Arens; Jordi Gonzalez |
Title |
Modeling vs. Learning Approaches for Monocular 3D Human Pose Estimation |
Type |
Conference Article |
Year |
2011 |
Publication |
1st IEEE International Workshop on Performance Evaluation on Recognition of Human Actions and Pose Estimation Methods |
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London, United Kingdom |
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PERHAPS |
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ISE |
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no |
Call Number |
Admin @ si @ GBA2011 |
Serial |
1812 |
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Author |
Jordi Gonzalez; Josep M. Gonfaus; Carles Fernandez; Xavier Roca |
Title |
Exploiting Natural-Language Interaction in Video Surveillance Systems |
Type |
Conference Article |
Year |
2011 |
Publication |
V&L Net Workshop on Vision and Language |
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Address |
Brighton, UK |
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VL |
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ISE |
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no |
Call Number |
Admin @ si @ GGF2011 |
Serial |
1813 |
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Author |
Murad Al Haj; Carles Fernandez; Zhanwu Xiong; Ivan Huerta; Jordi Gonzalez; Xavier Roca |
Title |
Beyond the Static Camera: Issues and Trends in Active Vision |
Type |
Book Chapter |
Year |
2011 |
Publication |
Visual Analysis of Humans: Looking at People |
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Issue |
2 |
Pages |
11-30 |
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Abstract |
Maximizing both the area coverage and the resolution per target is highly desirable in many applications of computer vision. However, with a limited number of cameras viewing a scene, the two objectives are contradictory. This chapter is dedicated to active vision systems, trying to achieve a trade-off between these two aims and examining the use of high-level reasoning in such scenarios. The chapter starts by introducing different approaches to active cameras configurations. Later, a single active camera system to track a moving object is developed, offering the reader first-hand understanding of the issues involved. Another section discusses practical considerations in building an active vision platform, taking as an example a multi-camera system developed for a European project. The last section of the chapter reflects upon the future trends of using semantic factors to drive smartly coordinated active systems. |
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Springer London |
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Editor |
Th.B. Moeslund; A. Hilton; V. Krüger; L. Sigal |
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ISBN |
978-0-85729-996-3 |
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ISE |
Approved |
no |
Call Number |
Admin @ si @ AFX2011 |
Serial |
1814 |
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Author |
Albert Gordo; Florent Perronnin |
Title |
Asymmetric Distances for Binary Embeddings |
Type |
Conference Article |
Year |
2011 |
Publication |
IEEE Conference on Computer Vision and Pattern Recognition |
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Issue |
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Pages |
729 - 736 |
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Abstract |
In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH) and Semi-Supervised Hashing (SSH). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques. We also propose a novel simple binary embedding technique – PCA Embedding (PCAE) – which is shown to yield competitive results with respect to more complex algorithms such as SH and SSH. |
Address |
Providence, RI |
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ISBN |
978-1-4577-0394-2 |
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Conference |
CVPR |
Notes |
DAG |
Approved |
no |
Call Number |
Admin @ si @ GoP2011; IAM @ iam @ GoP2011 |
Serial |
1817 |
Permanent link to this record |
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Author |
Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny |
Title |
Descriptor-based Svm Wall Detector |
Type |
Conference Article |
Year |
2011 |
Publication |
9th International Workshop on Graphic Recognition |
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Abstract |
Architectural floorplans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. In this paper we describe an evolution of this new approach in two directions: firstly we evaluate different features to obtain the description of every patch. Secondly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These modifications of the method have been tested for wall detection on two datasets of architectural floorplans with different notations and compared with the results obtained with the original approach. |
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GREC |
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DAG |
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no |
Call Number |
Admin @ si @ HMS2011b |
Serial |
1819 |
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Author |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
Title |
Classification of Administrative Document Images by Logo Identification |
Type |
Conference Article |
Year |
2011 |
Publication |
In proceedings of 9th IAPR Workshop on Graphic Recognition |
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This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. |
Address |
Seoul, Corea |
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GREC |
Notes |
DAG |
Approved |
no |
Call Number |
Admin @ si @ RPK2011 |
Serial |
1821 |
Permanent link to this record |
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Author |
Alicia Fornes; Volkmar Frinken; Andreas Fischer; Jon Almazan; G. Jackson; Horst Bunke |
Title |
A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors |
Type |
Conference Article |
Year |
2011 |
Publication |
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing |
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Issue |
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Pages |
83-90 |
Keywords |
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Abstract |
The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach. |
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Publisher |
ACM |
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ISBN |
978-1-4503-0916-5 |
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HIP |
Notes |
DAG |
Approved |
no |
Call Number |
Admin @ si @ FFF2011a |
Serial |
1823 |
Permanent link to this record |