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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 |
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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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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 |
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no |
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DAG @ dag @ RNK2010 |
Serial |
1435 |
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Author |
Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard |
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Title |
A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video |
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Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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Volume |
6388 |
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Pages |
93–98 |
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We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR. |
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Springer, Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-17710-1 |
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no |
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DAG @ dag @ LLR2010 |
Serial |
1459 |
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Author |
Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados |
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Title |
A Content Spotting System For Line Drawing Graphic Document Images |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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Volume |
20 |
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Pages |
3420–3423 |
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We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize the documents in the repository, represent them by attributed relational graphs, extract regions of interest (ROIs) from them, convert each ROI to a fuzzy structural signature, cluster similar signatures to form ROI classes and build an index for the repository. During online querying mode: a Bayesian network classifier recognizes the ROIs in the query image and the corresponding documents are fetched by looking up in the repository index. Experimental results are presented for synthetic images of architectural and electronic documents. |
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1051-4651 |
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978-1-4244-7542-1 |
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no |
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DAG @ dag @ LBR2010b |
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1460 |
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Author |
Albert Gordo; Florent Perronnin |
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Title |
A Bag-of-Pages Approach to Unordered Multi-Page Document Classification |
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Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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Pages |
1920–1923 |
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We consider the problem of classifying documents containing multiple unordered pages. For this purpose, we propose a novel bag-of-pages document representation. To represent a document, one assigns every page to a prototype in a codebook of pages. This leads to a histogram representation which can then be fed to any discriminative classifier. We also consider several refinements over this initial approach. We show on two challenging datasets that the proposed approach significantly outperforms a baseline system. |
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Istanbul (Turkey) |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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DAG |
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no |
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Admin @ si @ GoP2010 |
Serial |
1480 |
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Author |
H. Chouaib; Oriol Ramos Terrades; Salvatore Tabbone; F. Cloppet; N. Vincent |
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Title |
Feature Selection Combining Genetic Algorithm and Adaboost Classifiers |
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Conference Article |
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Year |
2008 |
Publication |
19th International Conference on Pattern Recognition |
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1-4 |
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Tampa, Florida |
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DAG |
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no |
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Call Number |
Admin @ si @ CRT2008 |
Serial |
1872 |
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Author |
Salvatore Tabbone; Oriol Ramos Terrades; S. Barrat |
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Title |
Histogram of radon transform. A useful descriptor for shape retrieval |
Type |
Conference Article |
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Year |
2008 |
Publication |
19th International Conference on Pattern Recognition |
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1-4 |
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Tampa, Florida |
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DAG |
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no |
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Call Number |
Admin @ si @ TRB2008 |
Serial |
1876 |
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Author |
David Vazquez; Antonio Lopez; Daniel Ponsa |
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Title |
Unsupervised Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
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Pages |
3492 - 3495 |
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Keywords |
Pedestrian Detection; Domain Adaptation; Virtual worlds |
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Abstract |
Vision-based object detectors are crucial for different applications. They rely on learnt object models. Ideally, we would like to deploy our vision system in the scenario where it must operate, and lead it to self-learn how to distinguish the objects of interest, i.e., without human intervention. However, the learning of each object model requires labelled samples collected through a tiresome manual process. For instance, we are interested in exploring the self-training of a pedestrian detector for driver assistance systems. Our first approach to avoid manual labelling consisted in the use of samples coming from realistic computer graphics, so that their labels are automatically available [12]. This would make possible the desired self-training of our pedestrian detector. However, as we showed in [14], between virtual and real worlds it may be a dataset shift. In order to overcome it, we propose the use of unsupervised domain adaptation techniques that avoid human intervention during the adaptation process. In particular, this paper explores the use of the transductive SVM (T-SVM) learning algorithm in order to adapt virtual and real worlds for pedestrian detection (Fig. 1). |
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Tsukuba Science City, Japan |
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IEEE |
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Tsukuba Science City, JAPAN |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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ADAS |
Approved |
no |
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ADAS @ adas @ VLP2012 |
Serial |
1981 |
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Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez; N. Paragios |
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Title |
Image Contextual Representation and Matching through Hierarchies and Higher Order Graphs |
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Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
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Pages |
2664 - 2667 |
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We present a region matching algorithm which establishes correspondences between regions from two segmented images. An abstract graph-based representation conceals the image in a hierarchical graph, exploiting the scene properties at two levels. First, the similarity and spatial consistency of the image semantic objects is encoded in a graph of commute times. Second, the cluttered regions of the semantic objects are represented with a shape descriptor. Many-to-many matching of regions is specially challenging due to the instability of the segmentation under slight image changes, and we explicitly handle it through high order potentials. We demonstrate the matching approach applied to images of world famous buildings, captured under different conditions, showing the robustness of our method to large variations in illumination and viewpoint. |
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Tsukuba Science City, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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ADAS |
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no |
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Call Number |
Admin @ si @ RSL2012a; |
Serial |
2032 |
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Author |
German Ros; Jesus Martinez del Rincon; Gines Garcia-Mateos |
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Title |
Articulated Particle Filter for Hand Tracking |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
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3581 - 3585 |
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This paper proposes a new version of Particle Filter, called Articulated Particle Filter – ArPF -, which has been specifically designed for an efficient sampling of hierarchical spaces, generated by articulated objects. Our approach decomposes the articulated motion into layers for efficiency purposes, making use of a careful modeling of the diffusion noise along with its propagation through the articulations. This produces an increase of accuracy and prevent for divergences. The algorithm is tested on hand tracking due to its complex hierarchical articulated nature. With this purpose, a new dataset generation tool for quantitative evaluation is also presented in this paper. |
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Tsukuba Science City, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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ADAS |
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no |
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Call Number |
Admin @ si @ RMG2012 |
Serial |
2031 |
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Author |
Francisco Cruz; Oriol Ramos Terrades |
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Title |
Document segmentation using relative location features |
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Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
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Pages |
1562-1565 |
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In this paper we evaluate the use of Relative Location Features (RLF) on a historical document segmentation task, and compare the quality of the results obtained on structured and unstructured documents using RLF and not using them. We prove that using these features improve the final segmentation on documents with a strong structure, while their application on unstructured documents does not show significant improvement. Although this paper is not focused on segmenting unstructured documents, results obtained on a benchmark dataset are equal or even overcome previous results of similar works. |
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Tsukuba Science City, Japan |
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DAG |
Approved |
no |
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Call Number |
Admin @ si @ CrR2012 |
Serial |
2051 |
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Author |
Volkmar Frinken; Francisco Zamora; Salvador España; Maria Jose Castro; Andreas Fischer; Horst Bunke |
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Title |
Long-Short Term Memory Neural Networks Language Modeling for Handwriting Recognition |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
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Pages |
701-704 |
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Unconstrained handwritten text recognition systems maximize the combination of two separate probability scores. The first one is the observation probability that indicates how well the returned word sequence matches the input image. The second score is the probability that reflects how likely a word sequence is according to a language model. Current state-of-the-art recognition systems use statistical language models in form of bigram word probabilities. This paper proposes to model the target language by means of a recurrent neural network with long-short term memory cells. Because the network is recurrent, the considered context is not limited to a fixed size especially as the memory cells are designed to deal with long-term dependencies. In a set of experiments conducted on the IAM off-line database we show the superiority of the proposed language model over statistical n-gram models. |
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Tsukuba Science City, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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DAG |
Approved |
no |
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Admin @ si @ FZE2012 |
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2052 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Andrew Bagdanov; Josep Llados |
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Title |
Multipage Document Retrieval by Textual and Visual Representations |
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Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
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521-524 |
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In this paper we present a multipage administrative document image retrieval system based on textual and visual representations of document pages. Individual pages are represented by textual or visual information using a bag-of-words framework. Different fusion strategies are evaluated which allow the system to perform multipage document retrieval on the basis of a single page retrieval system. Results are reported on a large dataset of document images sampled from a banking workflow. |
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Tsukuba Science City, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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DAG |
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no |
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Admin @ si @ RKB2012 |
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2053 |
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Author |
Antonio Hernandez; Miguel Angel Bautista; Xavier Perez Sala; Victor Ponce; Xavier Baro; Oriol Pujol; Cecilio Angulo; Sergio Escalera |
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Title |
BoVDW: Bag-of-Visual-and-Depth-Words for Gesture Recognition |
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Conference Article |
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2012 |
Publication |
21st International Conference on Pattern Recognition |
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We present a Bag-of-Visual-and-Depth-Words (BoVDW) model for gesture recognition, an extension of the Bag-of-Visual-Words (BoVW) model, that benefits from the multimodal fusion of visual and depth features. State-of-the-art RGB and depth features, including a new proposed depth descriptor, are analysed and combined in a late fusion fashion. The method is integrated in a continuous gesture recognition pipeline, where Dynamic Time Warping (DTW) algorithm is used to perform prior segmentation of gestures. Results of the method in public data sets, within our gesture recognition pipeline, show better performance in comparison to a standard BoVW model. |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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HuPBA;MV |
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no |
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Admin @ si @ HBP2012 |
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2122 |
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Author |
Anjan Dutta; Jaume Gibert; Josep Llados; Horst Bunke; Umapada Pal |
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Title |
Combination of Product Graph and Random Walk Kernel for Symbol Spotting in Graphical Documents |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
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1663-1666 |
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This paper explores the utilization of product graph for spotting symbols on graphical documents. Product graph is intended to find the candidate subgraphs or components in the input graph containing the paths similar to the query graph. The acute angle between two edges and their length ratio are considered as the node labels. In a second step, each of the candidate subgraphs in the input graph is assigned with a distance measure computed by a random walk kernel. Actually it is the minimum of the distances of the component to all the components of the model graph. This distance measure is then used to eliminate dissimilar components. The remaining neighboring components are grouped and the grouped zone is considered as a retrieval zone of a symbol similar to the queried one. The entire method works online, i.e., it doesn't need any preprocessing step. The present paper reports the initial results of the method, which are very encouraging. |
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Tsukuba, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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DAG |
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Admin @ si @ DGL2012 |
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2125 |
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Author |
Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades |
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Title |
Text/graphic separation using a sparse representation with multi-learned dictionaries |
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Conference Article |
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2012 |
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21st International Conference on Pattern Recognition |
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Graphics Recognition; Layout Analysis; Document Understandin |
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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. |
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Tsukuba |
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no |
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Admin @ si @ DTR2012a |
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2135 |
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