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Author |
Diego Alejandro Cheda; Daniel Ponsa; Antonio Lopez |
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Title |
Camera Egomotion Estimation in the ADAS Context |
Type |
Conference Article |
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Year |
2010 |
Publication |
13th International IEEE Annual Conference on Intelligent Transportation Systems |
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Issue |
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Pages |
1415–1420 |
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Abstract |
Camera-based Advanced Driver Assistance Systems (ADAS) have concentrated many research efforts in the last decades. Proposals based on monocular cameras require the knowledge of the camera pose with respect to the environment, in order to reach an efficient and robust performance. A common assumption in such systems is considering the road as planar, and the camera pose with respect to it as approximately known. However, in real situations, the camera pose varies along time due to the vehicle movement, the road slope, and irregularities on the road surface. Thus, the changes in the camera position and orientation (i.e., the egomotion) are critical information that must be estimated at every frame to avoid poor performances. This work focuses on egomotion estimation from a monocular camera under the ADAS context. We review and compare egomotion methods with simulated and real ADAS-like sequences. Basing on the results of our experiments, we show which of the considered nonlinear and linear algorithms have the best performance in this domain. |
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Madeira Island (Portugal) |
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Edition |
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ISSN |
2153-0009 |
ISBN |
978-1-4244-7657-2 |
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ITSC |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ CPL2010 |
Serial |
1425 |
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Permanent link to this record |
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Author |
Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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Title |
Perceptual color texture codebooks for retrieving in highly diverse texture datasets |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
866–869 |
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Abstract |
Color and texture are visual cues of different nature, their integration in a useful visual descriptor is not an obvious step. One way to combine both features is to compute texture descriptors independently on each color channel. A second way is integrate the features at a descriptor level, in this case arises the problem of normalizing both cues. A significant progress in the last years in object recognition has provided the bag-of-words framework that again deals with the problem of feature combination through the definition of vocabularies of visual words. Inspired in this framework, here we present perceptual textons that will allow to fuse color and texture at the level of p-blobs, which is our feature detection step. Feature representation is based on two uniform spaces representing the attributes of the p-blobs. The low-dimensionality of these text on spaces will allow to bypass the usual problems of previous approaches. Firstly, no need for normalization between cues; and secondly, vocabularies are directly obtained from the perceptual properties of text on spaces without any learning step. Our proposal improve current state-of-art of color-texture descriptors in an image retrieval experiment over a highly diverse texture dataset from Corel. |
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Address |
Istanbul (Turkey) |
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Edition |
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ISSN |
1051-4651 |
ISBN |
978-1-4244-7542-1 |
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ICPR |
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CIC |
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no |
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Call Number |
CAT @ cat @ ASV2010b |
Serial |
1426 |
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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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Volume |
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Pages |
377–384 |
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Abstract |
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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DAS |
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DAG |
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no |
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Call Number |
DAG @ dag @ GGV2010 |
Serial |
1431 |
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Permanent link to this record |
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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 |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
19–26 |
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Abstract |
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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DAS |
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DAG |
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no |
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Call Number |
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 |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
191–198 |
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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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Address |
Boston; USA |
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ISBN |
978-1-60558-773-8 |
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DAS |
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Notes |
DAG |
Approved |
no |
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Call Number |
DAG @ dag @ RPL2010b |
Serial |
1433 |
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Permanent link to this record |
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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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Volume |
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Issue |
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Pages |
215–222 |
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Keywords |
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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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Address |
Boston; USA |
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DAS |
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Notes |
DAG |
Approved |
no |
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Call Number |
DAG @ dag @ RuL2010b |
Serial |
1434 |
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Permanent link to this record |
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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 |
Abbreviated Journal |
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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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Address |
Istanbul (Turkey) |
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ISSN |
1051-4651 |
ISBN |
978-1-4244-7542-1 |
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Conference |
ICPR |
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Notes |
DAG |
Approved |
no |
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Call Number |
DAG @ dag @ RNK2010 |
Serial |
1435 |
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Permanent link to this record |
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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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Abstract |
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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Notes |
DAG |
Approved |
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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Volume |
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Pages |
167–174 |
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Abstract |
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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Address |
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 |
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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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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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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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0302-9743 |
ISBN |
978-3-642-15551-2 |
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ECCV |
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ISE |
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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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Pages |
1–12 |
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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 |
Joan Mas; Gemma Sanchez; Josep Llados |
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Title |
SSP: Sketching slide Presentations, a Syntactic Approach |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
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The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide. |
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La Rochelle; France; July 2009 |
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DAG @ dag @ MSL2009a |
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1441 |
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Salim Jouili; Salvatore Tabbone; Ernest Valveny |
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Comparing Graph Similarity Measures for Graphical Recognition. |
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2009 |
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8th IAPR International Workshop on Graphics Recognition |
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In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique. |
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La Rochelle; France; July 2009 |
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Springer |
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DAG @ dag @ JTV2009 |
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1442 |
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Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman |
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A Performance Characterization Algorithm for Symbol Localization |
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2009 |
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8th IAPR International Workshop on Graphics Recognition |
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3-11 |
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In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols). |
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La Rochelle; July 2009 |
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DAG @ dag @ DRV2009 |
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1443 |
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