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Author |
Albert Gordo; Jaume Gibert; Ernest Valveny; Marçal Rusiñol |
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Title |
A Kernel-based Approach to Document Retrieval |
Type |
Conference Article |
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Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
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Pages |
377–384 |
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In this paper we tackle the problem of document image retrieval by combining a similarity measure between documents and the probability that a given document belongs to a certain class. The membership probability to a specific class is computed using Support Vector Machines in conjunction with similarity measure based kernel applied to structural document representations. In the presented experiments, we use different document representations, both visual and structural, and we apply them to a database of historical documents. We show how our method based on similarity kernels outperforms the usual distance-based retrieval. |
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Boston; USA; |
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978-1-60558-773-8 |
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DAG |
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no |
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DAG @ dag @ GGV2010 |
Serial |
1431 |
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Author |
Antonio Clavelli; Dimosthenis Karatzas; Josep Llados |
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Title |
A framework for the assessment of text extraction algorithms on complex colour images |
Type |
Conference Article |
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Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
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Pages |
19–26 |
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The availability of open, ground-truthed datasets and clear performance metrics is a crucial factor in the development of an application domain. The domain of colour text image analysis (real scenes, Web and spam images, scanned colour documents) has traditionally suffered from a lack of a comprehensive performance evaluation framework. Such a framework is extremely difficult to specify, and corresponding pixel-level accurate information tedious to define. In this paper we discuss the challenges and technical issues associated with developing such a framework. Then, we describe a complete framework for the evaluation of text extraction methods at multiple levels, provide a detailed ground-truth specification and present a case study on how this framework can be used in a real-life situation. |
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Boston; USA; |
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978-1-60558-773-8 |
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DAG |
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no |
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DAG @ dag @ CKL2010 |
Serial |
1432 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Query Driven Word Retrieval in Graphical Documents |
Type |
Conference Article |
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Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
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Pages |
191–198 |
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In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents. |
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Boston; USA |
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978-1-60558-773-8 |
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DAG |
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no |
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Call Number |
DAG @ dag @ RPL2010b |
Serial |
1433 |
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Author |
Marçal Rusiñol; Josep Llados |
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Title |
Efficient Logo Retrieval Through Hashing Shape Context Descriptors |
Type |
Conference Article |
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Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
Abbreviated Journal |
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Pages |
215–222 |
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Abstract |
In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents. |
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Boston; USA |
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DAG |
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no |
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Call Number |
DAG @ dag @ RuL2010b |
Serial |
1434 |
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Author |
Marçal Rusiñol; Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny; Josep Llados |
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Title |
Perceptual Image Retrieval by Adding Color Information to the Shape Context Descriptor |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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Pages |
1594–1597 |
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Abstract |
In this paper we present a method for the retrieval of images in terms of perceptual similarity. Local color information is added to the shape context descriptor in order to obtain an object description integrating both shape and color as visual cues. We use a color naming algorithm in order to represent the color information from a perceptual point of view. The proposed method has been tested in two different applications, an object retrieval scenario based on color sketch queries and a color trademark retrieval problem. Experimental results show that the addition of the color information significantly outperforms the sole use of the shape context descriptor. |
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Istanbul (Turkey) |
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ISSN |
1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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DAG |
Approved |
no |
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Call Number |
DAG @ dag @ RNK2010 |
Serial |
1435 |
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Author |
Farshad Nourbakhsh; Dimosthenis Karatzas; Ernest Valveny |
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Title |
A polar-based logo representation based on topological and colour features |
Type |
Conference Article |
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Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
Abbreviated Journal |
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Pages |
341–348 |
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In this paper, we propose a novel rotation and scale invariant method for colour logo retrieval and classification, which involves performing a simple colour segmentation and subsequently describing each of the resultant colour components based on a set of topological and colour features. A polar representation is used to represent the logo and the subsequent logo matching is based on Cyclic Dynamic Time Warping (CDTW). We also show how combining information about the global distribution of the logo components and their local neighbourhood using the Delaunay triangulation allows to improve the results. All experiments are performed on a dataset of 2500 instances of 100 colour logo images in different rotations and scales. |
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Boston; USA; |
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ISBN |
978-1-60558-773-8 |
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DAS |
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DAG |
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no |
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Call Number |
DAG @ dag @ NKV2010 |
Serial |
1436 |
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Permanent link to this record |
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Author |
Sebastien Mace; Herve Locteau; Ernest Valveny; Salvatore Tabbone |
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Title |
A system to detect rooms in architectural floor plan images |
Type |
Conference Article |
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Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
Abbreviated Journal |
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Pages |
167–174 |
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In this article, a system to detect rooms in architectural floor plan images is described. We first present a primitive extraction algorithm for line detection. It is based on an original coupling of classical Hough transform with image vectorization in order to perform robust and efficient line detection. We show how the lines that satisfy some graphical arrangements are combined into walls. We also present the way we detect some door hypothesis thanks to the extraction of arcs. Walls and door hypothesis are then used by our room segmentation strategy; it consists in recursively decomposing the image until getting nearly convex regions. The notion of convexity is difficult to quantify, and the selection of separation lines between regions can also be rough. We take advantage of knowledge associated to architectural floor plans in order to obtain mostly rectangular rooms. Qualitative and quantitative evaluations performed on a corpus of real documents show promising results. |
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Boston; USA |
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978-1-60558-773-8 |
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DAS |
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DAG |
Approved |
no |
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Call Number |
DAG @ dag @ MLV2010 |
Serial |
1437 |
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Permanent link to this record |
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Author |
Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva |
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Title |
Recursive Coarse-to-Fine Localization for fast Object Recognition |
Type |
Conference Article |
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Year |
2010 |
Publication |
11th European Conference on Computer Vision |
Abbreviated Journal |
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Volume |
6313 |
Issue |
II |
Pages |
280–293 |
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Abstract |
Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors and corresponding thresholds to learn. Furthermore, they do not use any prior knowledge about the scene structure to decide where to focus the search. To handle these problems, we propose a new way to scan an image, where we couple a recursive coarse-to-fine refinement together with spatial constraints of the object location. For doing that we split an image into a set of uniformly distributed neighborhood regions, and for each of these we apply a local greedy search over feature resolutions. The neighborhood is defined as a scanning region that only one object can occupy. Therefore the best hypothesis is obtained as the location with maximum score and no thresholds are needed. We present an implementation of our method using a pyramid of HOG features and we evaluate it on two standard databases, VOC2007 and INRIA dataset. Results show that the Recursive Coarse-to-Fine Localization (RCFL) achieves a 12x speed-up compared to standard sliding windows. Compared with a cascade of multiple resolutions approach our method has slightly better performance in speed and Average-Precision. Furthermore, in contrast to cascading approach, the speed-up is independent of image conditions, the number of detected objects and clutter. |
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Address |
Crete (Greece) |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-15566-6 |
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ECCV |
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Notes |
ISE |
Approved |
no |
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Call Number |
DAG @ dag @ PGB2010 |
Serial |
1438 |
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Permanent link to this record |
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Author |
Carles Fernandez; Jordi Gonzalez; Xavier Roca |
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Title |
Automatic Learning of Background Semantics in Generic Surveilled Scenes |
Type |
Conference Article |
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Year |
2010 |
Publication |
11th European Conference on Computer Vision |
Abbreviated Journal |
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Volume |
6313 |
Issue |
II |
Pages |
678–692 |
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Abstract |
Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analysis techniques statistically infer semantics in locations where motion occurs, and such inferences are typically limited to abnormality. Thus, it is interesting to design contributions that automatically categorize more specific semantic regions. State-of-the-art approaches for unsupervised scene labeling exploit trajectory data to segment areas like sources, sinks, or waiting zones. Our method, in addition, incorporates scene-independent knowledge to assign more meaningful labels like crosswalks, sidewalks, or parking spaces. First, a spatiotemporal scene model is obtained from trajectory analysis. Subsequently, a so-called GI-MRF inference process reinforces spatial coherence, and incorporates taxonomy-guided smoothness constraints. Our method achieves automatic and effective labeling of conceptual regions in urban scenarios, and is robust to tracking errors. Experimental validation on 5 surveillance databases has been conducted to assess the generality and accuracy of the segmentations. The resulting scene models are used for model-based behavior analysis. |
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Address |
Crete (Greece) |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-15551-2 |
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ECCV |
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Notes |
ISE |
Approved |
no |
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Call Number |
ISE @ ise @ FGR2010 |
Serial |
1439 |
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Permanent link to this record |
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Author |
Herve Locteau; Sebastien Mace; Ernest Valveny; Salvatore Tabbone |
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Title |
Extraction des pieces de un plan de habitation |
Type |
Conference Article |
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Year |
2010 |
Publication |
Colloque Internacional Francophone de l´Ecrit et le Document |
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Volume |
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Pages |
1–12 |
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Abstract |
In this article, a method to extract the rooms of an architectural floor plan image is described. We first present a line detection algorithm to extract long lines in the image. Those lines are analyzed to identify the existing walls. From this point, room extraction can be seen as a classical segmentation task for which each region corresponds to a room. The chosen resolution strategy consists in recursively decomposing the image until getting nearly convex regions. The notion of convexity is difficult to quantify, and the selection of separation lines can also be rough. Thus, we take advantage of knowledge associated to architectural floor plans in order to obtain mainly rectangular rooms. Preliminary tests on a set of real documents show promising results. |
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Address |
Sousse, Tunisia |
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CIFED |
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Notes |
DAG |
Approved |
no |
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Call Number |
DAG @ dag @ LMV2010 |
Serial |
1440 |
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Permanent link to this record |
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Author |
Carlo Gatta; Simone Balocco; Francesco Ciompi; R. Hemetsberger; Oriol Rodriguez-Leor; Petia Radeva |
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Title |
Real-time gating of IVUS sequences based on motion blur analysis: Method and quantitative validation |
Type |
Conference Article |
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Year |
2010 |
Publication |
13th international conference on Medical image computing and computer-assisted intervention |
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Volume |
II |
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59-67 |
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Intravascular Ultrasound (IVUS) is an image-guiding technique for cardiovascular diagnostic, providing cross-sectional images of vessels. During the acquisition, the catheter is pulled back (pullback) at a constant speed in order to acquire spatially subsequent images of the artery. However, during this procedure, the heart twist produces a swinging fluctuation of the probe position along the vessel axis. In this paper we propose a real-time gating algorithm based on the analysis of motion blur variations during the IVUS sequence. Quantitative tests performed on an in-vitro ground truth data base shown that our method is superior to state of the art algorithms both in computational speed and accuracy. |
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Springer-Verlag Berlin |
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MICCAI |
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MILAB |
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no |
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Call Number |
BCNPCL @ bcnpcl @ GBC2010 |
Serial |
1447 |
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Permanent link to this record |
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Author |
Eloi Puertas; Sergio Escalera; Oriol Pujol |
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Title |
Classifying Objects at Different Sizes with Multi-Scale Stacked Sequential Learning |
Type |
Conference Article |
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Year |
2010 |
Publication |
13th International Conference of the Catalan Association for Artificial Intelligence |
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Volume |
220 |
Issue |
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Pages |
193–200 |
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Sequential learning is that discipline of machine learning that deals with dependent data. In this paper, we use the Multi-scale Stacked Sequential Learning approach (MSSL) to solve the task of pixel-wise classification based on contextual information. The main contribution of this work is a shifting technique applied during the testing phase that makes possible, thanks to template images, to classify objects at different sizes. The results show that the proposed method robustly classifies such objects capturing their spatial relationships. |
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Editor |
R. Alquezar, A. Moreno, J. Aguilar |
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978-1-60750-642-3 |
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CCIA |
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Notes |
HUPBA;MILAB |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ PEP2010 |
Serial |
1448 |
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Permanent link to this record |
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Author |
Sergio Escalera; Oriol Pujol; Eric Laciar; Jordi Vitria; Esther Pueyo; Petia Radeva |
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Title |
Classification of Coronary Damage in Chronic Chagasic Patients |
Type |
Book Chapter |
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Year |
2010 |
Publication |
Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence |
Abbreviated Journal |
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Volume |
299 |
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Pages |
461-478 |
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Keywords |
Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding |
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Abstract |
Post Conference IEEE-IS 2008
The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper,
we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs. |
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Springer-Verlag |
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V. Sgurev, M. Hadjiski (eds) |
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OR;MILAB;HUPBA;MV |
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BCNPCL @ bcnpcl @ EPL2010 |
Serial |
1452 |
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Author |
Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva |
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Title |
Conditional Random Fields for image segmentation in Intravascular Ultrasound |
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Conference Article |
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Year |
2010 |
Publication |
Medical Image Computing in Catalunya: Graduate Student Workshop |
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Pages |
13–14 |
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Abstract |
We present a Conditional Random Fields based approach for segmenting Intravascular Ultrasond (IVUS) images. The presented method uses a contextual discriminative graphical model to deal with the presence of distorsions and artifacts in IVUS images, that turns the segmentation of interesting regions into a difficult task. An accurate lumen segmentation on IVUS longitudinal images is achieved. |
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Girona |
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Conference |
MICCAT |
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Notes |
MILAB;HUPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ CPF2010 |
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1453 |
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Author |
Jose Manuel Alvarez |
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Title |
Combining Context and Appearance for Road Detection |
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Book Whole |
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Year |
2010 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Road traffic crashes have become a major cause of death and injury throughout the world.
Hence, in order to improve road safety, the automobile manufacture is moving towards the
development of vehicles with autonomous functionalities such as keeping in the right lane, safe distance keeping between vehicles or regulating the speed of the vehicle according to the traffic conditions. A key component of these systems is vision–based road detection that aims to detect the free road surface ahead the moving vehicle. Detecting the road using a monocular vision system is very challenging since the road is an outdoor scenario imaged from a mobile platform. Hence, the detection algorithm must be able to deal with continuously changing imaging conditions such as the presence ofdifferent objects (vehicles, pedestrians), different environments (urban, highways, off–road), different road types (shape, color), and different imaging conditions (varying illumination, different viewpoints and changing weather conditions). Therefore, in this thesis, we focus on vision–based road detection using a single color camera. More precisely, we first focus on analyzing and grouping pixels according to their low–level properties. In this way, two different approaches are presented to exploit
color and photometric invariance. Then, we focus the research of the thesis on exploiting context information. This information provides relevant knowledge about the road not using pixel features from road regions but semantic information from the analysis of the scene.
In this way, we present two different approaches to infer the geometry of the road ahead
the moving vehicle. Finally, we focus on combining these context and appearance (color)
approaches to improve the overall performance of road detection algorithms. The qualitative and quantitative results presented in this thesis on real–world driving sequences show that the proposed method is robust to varying imaging conditions, road types and scenarios going beyond the state–of–the–art. |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Antonio Lopez;Theo Gevers |
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978-84-937261-8-8 |
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ADAS |
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no |
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Call Number |
Admin @ si @ Alv2010 |
Serial |
1454 |
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