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| Author | Miguel Reyes; Jose Ramirez Moreno; Juan R Revilla; Petia Radeva; Sergio Escalera | ||||
| Title | ADiBAS: Sistema Multisensor de Adquisicion Automatica de Datos Corporales Objetivos, Robustos y Fiables para el Analisis de la Postura y el Movimiento | Type | Conference Article | ||
| Year | 2011 | Publication | 6th Congreso Iberoamericano de Tecnologia de Apoyo a la Discapacidad | Abbreviated Journal | |
| Volume | Issue | Pages | 939-944 | ||
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| Abstract | El análisis de la postura y del rango de movimiento son fundamentales para conocer la optimización del gesto y mejorar, de este modo, el rendimiento y la detección de posibles lesiones. Esta cuantificación es especialmente interesante en deportistas o en pacientes que presentan alguna lesión neurológica o del sistema musculo-esquelético, ya que permite conocer el proceso evolutivo de estos pacientes, evaluar la eficacia de la terapia aplicada y proponer, en caso necesario, una modificación del protocolo de tratamiento.
En este trabajo presentamos un sistema automático que permite, mediante una tecnología no invasiva, la captación automática de marcadores LED situados sobre el paciente y su posterior análisis con el fin de mostrar al especialista datos objetivos que permitan un mejor soporte diagnóstico. También se describe un sistema analítico de la postura corporal sin marcadores, donde su ejecución durante secuencias dinámicas aporta un alto grado de naturalidad al paciente a la hora de realizar los ejercicios funcionales. |
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| Address | Palma de Mallorca | ||||
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IBERDISCAP | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ RRR2011 | Serial | 1768 | ||
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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| Year | 2011 | Publication | Proceedings of the 2011 Workshop on Historical Document Imaging and Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 83-90 | ||
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| Abstract | The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition.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 | Place of Publication | Editor | ||
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| ISSN | ISBN | 978-1-4503-0916-5 | Medium | ||
| Area | Expedition | Conference |
HIP | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ FFF2011a | Serial | 1823 | ||
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| Author | Andreas Fischer; Volkmar Frinken; Alicia Fornes; Horst Bunke | ||||
| Title | Transcription Alignment of Latin Manuscripts Using Hidden Markov Models | Type | Conference Article | ||
| Year | 2011 | Publication | Proceedings of the 2011 Workshop on Historical Document Imaging and Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 29-36 | ||
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| Abstract | Transcriptions of historical documents are a valuable source for extracting labeled handwriting images that can be used for training recognition systems. In this paper, we introduce the Saint Gall database that includes images as well as the transcription of a Latin manuscript from the 9th century written in Carolingian script. Although the available transcription is of high quality for a human reader, the spelling of the words is not accurate when compared with the handwriting image. Hence, the transcription poses several challenges for alignment regarding, e.g., line breaks, abbreviations, and capitalization. We propose an alignment system based on character Hidden Markov Models that can cope with these challenges and efficiently aligns complete document pages. On the Saint Gall database, we demonstrate that a considerable alignment accuracy can be achieved, even with weakly trained character models. | ||||
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| Publisher | ACM | Place of Publication | Editor | ||
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HIP | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ FFF2011b | Serial | 1824 | ||
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| Author | Antonio Hernandez; Carlos Primo; Sergio Escalera | ||||
| Title | Automatic user interaction correction via Multi-label Graph cuts | Type | Conference Article | ||
| Year | 2011 | Publication | In ICCV 2011 1st IEEE International Workshop on Human Interaction in Computer Vision HICV | Abbreviated Journal | |
| Volume | Issue | Pages | 1276-1281 | ||
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| Abstract | Most applications in image segmentation requires from user interaction in order to achieve accurate results. However, user wants to achieve the desired segmentation accuracy reducing effort of manual labelling. In this work, we extend standard multi-label α-expansion Graph Cut algorithm so that it analyzes the interaction of the user in order to modify the object model and improve final segmentation of objects. The approach is inspired in the fact that fast user interactions may introduce some pixel errors confusing object and background. Our results with different degrees of user interaction and input errors show high performance of the proposed approach on a multi-label human limb segmentation problem compared with classical α-expansion algorithm. | ||||
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| ISSN | ISBN | 978-1-4673-0062-9 | Medium | ||
| Area | Expedition | Conference |
HICV | ||
| Notes | MILAB; HuPBA | Approved | no | ||
| Call Number | Admin @ si @ HPE2011 | Serial | 1892 | ||
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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 | Abbreviated Journal | |
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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 | ||
| Notes | DAG | Approved | 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 | Abbreviated Journal | |
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| Abstract | 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 | ||
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| Author | Anjan Dutta; Josep Llados; Umapada Pal | ||||
| Title | Bag-of-GraphPaths Descriptors for Symbol Recognition and Spotting in Line Drawings | Type | Conference Article | ||
| Year | 2011 | Publication | In proceedings of 9th IAPR Workshop on Graphic Recognition | Abbreviated Journal | |
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| Abstract | Graphical symbol recognition and spotting recently have become an important research activity. In this work we present a descriptor for symbols, especially for line drawings. The descriptor is based on the graph representation of graphical objects. We construct graphs from the vectorized information of the binarized images, where the critical points detected by the vectorization algorithm are considered as nodes and the lines joining them are considered as edges. Graph paths between two nodes in a graph are the finite sequences of nodes following the order from the starting to the final node. The occurrences of different graph paths in a given graph is an important feature, as they capture the geometrical and structural attributes of a graph. So the graph representing a symbol can efficiently be represent by the occurrences of its different paths. Their occurrences in a symbol can be obtained in terms of a histogram counting the number of some fixed prototype paths, we call the histogram as the Bag-of-GraphPaths (BOGP). These BOGP histograms are used as a descriptor to measure the distance among the symbols in vector space. We use the descriptor for three applications, they are: (1) classification of the graphical symbols, (2) spotting of the architectural symbols on floorplans, (3) classification of the historical handwritten words. | ||||
| Address | Seoul, Korea | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-36823-3 | Medium | |
| Area | Expedition | Conference |
GREC | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ DLP2011c | Serial | 1825 | ||
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| Author | Oscar Amoros; Sergio Escalera; Anna Puig | ||||
| Title | Adaboost GPU-based Classifier for Direct Volume Rendering | Type | Conference Article | ||
| Year | 2011 | Publication | International Conference on Computer Graphics Theory and Applications | Abbreviated Journal | |
| Volume | Issue | Pages | 215-219 | ||
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| Abstract | In volume visualization, the voxel visibitity and materials are carried out through an interactive editing of Transfer Function. In this paper, we present a two-level GPU-based labeling method that computes in times of rendering a set of labeled structures using the Adaboost machine learning classifier. In a pre-processing step, Adaboost trains a binary classifier from a pre-labeled dataset and, in each sample, takes into account a set of features. This binary classifier is a weighted combination of weak classifiers, which can be expressed as simple decision functions estimated on a single feature values. Then, at the testing stage, each weak classifier is independently applied on the features of a set of unlabeled samples. We propose an alternative representation of these classifiers that allow a GPU-based parallelizated testing stage embedded into the visualization pipeline. The empirical results confirm the OpenCL-based classification of biomedical datasets as a tough problem where an opportunity for further research emerges. | ||||
| Address | Algarve, Portugal | ||||
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| Area | Expedition | Conference |
GRAPP | ||
| Notes | MILAB; HuPBA | Approved | no | ||
| Call Number | Admin @ si @ AEP2011 | Serial | 1774 | ||
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| Author | Jaume Gibert; Ernest Valveny; Horst Bunke | ||||
| Title | Dimensionality Reduction for Graph of Words Embedding | Type | Conference Article | ||
| Year | 2011 | Publication | 8th IAPR-TC-15 International Workshop. Graph-Based Representations in Pattern Recognition | Abbreviated Journal | |
| Volume | 6658 | Issue | Pages | 22-31 | |
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| Abstract | The Graph of Words Embedding consists in mapping every graph of a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. While it shows good properties in classification problems, it suffers from high dimensionality and sparsity. These two issues are addressed in this article. Two well-known techniques for dimensionality reduction, kernel principal component analysis (kPCA) and independent component analysis (ICA), are applied to the embedded graphs. We discuss their performance compared to the classification of the original vectors on three different public databases of graphs. | ||||
| Address | Münster, Germany | ||||
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| Publisher | Place of Publication | Editor | Xiaoyi Jiang; Miquel Ferrer; Andrea Torsello | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-642-20843-0 | Medium | ||
| Area | Expedition | Conference |
GbRPR | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ GVB2011a | Serial | 1743 | ||
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| Author | Gemma Roig; Xavier Boix; F. de la Torre; Joan Serrat; C. Vilella | ||||
| Title | Hierarchical CRF with product label spaces for parts-based Models | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE Conference on Automatic Face and Gesture Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 657-664 | ||
| Keywords | Shape; Computational modeling; Principal component analysis; Random variables; Color; Upper bound; Facial features | ||||
| Abstract | Non-rigid object detection is a challenging an open research problem in computer vision. It is a critical part in many applications such as image search, surveillance, human-computer interaction or image auto-annotation. Most successful approaches to non-rigid object detection make use of part-based models. In particular, Conditional Random Fields (CRF) have been successfully embedded into a discriminative parts-based model framework due to its effectiveness for learning and inference (usually based on a tree structure). However, CRF-based approaches do not incorporate global constraints and only model pairwise interactions. This is especially important when modeling object classes that may have complex parts interactions (e.g. facial features or body articulations), because neglecting them yields an oversimplified model with suboptimal performance. To overcome this limitation, this paper proposes a novel hierarchical CRF (HCRF). The main contribution is to build a hierarchy of part combinations by extending the label set to a hierarchy of product label spaces. In order to keep the inference computation tractable, we propose an effective method to reduce the new label set. We test our method on two applications: facial feature detection on the Multi-PIE database and human pose estimation on the Buffy dataset. | ||||
| Address | Santa Barbara, CA, USA, 2011 | ||||
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FG | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ RBT2011 | Serial | 1862 | ||
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| Author | Jordi Roca; C. Alejandro Parraga; Maria Vanrell | ||||
| Title | Categorical Focal Colours are Structurally Invariant Under Illuminant Changes | Type | Conference Article | ||
| Year | 2011 | Publication | European Conference on Visual Perception | Abbreviated Journal | |
| Volume | Issue | Pages | 196 | ||
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| Abstract | The visual system perceives the colour of surfaces approximately constant under changes of illumination. In this work, we investigate how stable is the perception of categorical \“focal\” colours and their interrelations with varying illuminants and simple chromatic backgrounds. It has been proposed that best examples of colour categories across languages cluster in small regions of the colour space and are restricted to a set of 11 basic terms (Kay and Regier, 2003 Proceedings of the National Academy of Sciences of the USA 100 9085\–9089). Following this, we developed a psychophysical paradigm that exploits the ability of subjects to reliably reproduce the most representative examples of each category, adjusting multiple test patches embedded in a coloured Mondrian. The experiment was run on a CRT monitor (inside a dark room) under various simulated illuminants. We modelled the recorded data for each subject and adapted state as a 3D interconnected structure (graph) in Lab space. The graph nodes were the subject\’s focal colours at each adaptation state. The model allowed us to get a better distance measure between focal structures under different illuminants. We found that perceptual focal structures tend to be preserved better than the structures of the physical \“ideal\” colours under illuminant changes. | ||||
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| Series Editor | Series Title | Perception 40 | Abbreviated Series Title | ||
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| Area | Expedition | Conference |
ECVP | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ RPV2011 | Serial | 1867 | ||
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| Author | Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados | ||||
| Title | Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval | Type | Conference Article | ||
| Year | 2011 | Publication | 33rd European Conference on Information Retrieval | Abbreviated Journal | |
| Volume | 6611 | Issue | Pages | 314-325 | |
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| Abstract | In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset. | ||||
| Address | Dublin, Ireland | ||||
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| Publisher | Springer | Place of Publication | Berlin | Editor | P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-642-20160-8 | Medium | ||
| Area | Expedition | Conference |
ECIR | ||
| Notes | DAG; RV;ADAS | Approved | no | ||
| Call Number | Admin @ si @ RAK2011 | Serial | 1737 | ||
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| Author | David Roche; Debora Gil; Jesus Giraldo | ||||
| Title | Using statistical inference for designing termination conditions ensuring convergence of Evolutionary Algorithms | Type | Conference Article | ||
| Year | 2011 | Publication | 11th European Conference on Artificial Life | Abbreviated Journal | |
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| Abstract | A main challenge in Evolutionary Algorithms (EAs) is determining a termination condition ensuring stabilization close to the optimum in real-world applications. Although for known test functions distribution-based quantities are good candidates (as far as suitable parameters are used), in real-world problems an open question still remains unsolved. How can we estimate an upper-bound for the termination condition value ensuring a given accuracy for the (unknown) EA solution?
We claim that the termination problem would be fully solved if we defined a quantity (depending only on the EA output) behaving like the solution accuracy. The open question would be, then, satisfactorily answered if we had a model relating both quantities, since accuracy could be predicted from the alternative quantity. We present a statistical inference framework addressing two topics: checking the correlation between the two quantities and defining a regression model for predicting (at a given confidence level) accuracy values from the EA output. |
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| Address | Paris, France | ||||
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ECAL | ||
| Notes | IAM; | Approved | no | ||
| Call Number | IAM @ iam @ RGG2011b | Serial | 1678 | ||
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| Author | Jaime Moreno; Xavier Otazu | ||||
| Title | Image coder based on Hilbert scanning of embedded quadTrees | Type | Conference Article | ||
| Year | 2011 | Publication | Data Compression Conference | Abbreviated Journal | |
| Volume | Issue | Pages | 470-470 | ||
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| Abstract | In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. | ||||
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DCC | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MoO2011b | Serial | 2177 | ||
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| Author | David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin | ||||
| Title | Cool world: domain adaptation of virtual and real worlds for human detection using active learning | Type | Conference Article | ||
| Year | 2011 | Publication | NIPS Domain Adaptation Workshop: Theory and Application | Abbreviated Journal | NIPS-DA |
| Volume | Issue | Pages | |||
| Keywords | Pedestrian Detection; Virtual; Domain Adaptation; Active Learning | ||||
| Abstract | Image based human detection is of paramount interest for different applications. The most promising human detectors rely on discriminatively learnt classifiers, i.e., trained with labelled samples. However, labelling is a manual intensive task, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, in Marin et al. we have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera and the same type of scenario. Accordingly, in Vazquez et al. we cast the problem as one of supervised domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we use an active learning technique. Thus, ultimately our human model is learnt by the combination of virtual- and real-world labelled samples which, to the best of our knowledge, was not done before. Here, we term such combined space cool world. In this extended abstract we summarize our proposal, and include quantitative results from Vazquez et al. showing its validity. | ||||
| Address | Granada, Spain | ||||
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| Publisher | Place of Publication | Granada, Spain | Editor | ||
| Language | English | Summary Language | English | Original Title | |
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DA-NIPS | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ VLP2011b | Serial | 1756 | ||
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