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| Author | Sergio Escalera; Petia Radeva; Jordi Vitria; Xavier Baro; Bogdan Raducanu | ||||
| Title | Modelling and Analyzing Multimodal Dyadic Interactions Using Social Networks | Type | Conference Article | ||
| Year | 2010 | Publication | 12th International Conference on Multimodal Interfaces and 7th Workshop on Machine Learning for Multimodal Interaction. | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Social interaction; Multimodal fusion, Influence model; Social network analysis | ||||
| Abstract | Social network analysis became a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from
multimodal dyadic interactions. First, speech detection is performed through an audio/visual fusion scheme based on stacked sequential learning. In the audio domain, speech is detected through clusterization of audio features. Clusters are modelled by means of an One-state Hidden Markov Model containing a diagonal covariance Gaussian Mixture Model. In the visual domain, speech detection is performed through differential-based feature extraction from the segmented mouth region, and a dynamic programming matching procedure. Second, in order to model the dyadic interactions, we employed the Influence Model whose states encode the previous integrated audio/visual data. Third, the social network is extracted based on the estimated influences. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The results are reported both in terms of accuracy of the audio/visual data fusion and centrality measures used to characterize the social network. |
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| Address | Beijing (China) | ||||
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| Area | Expedition | Conference | ICMI-MLI | ||
| Notes | OR;MILAB;HUPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ ERV2010 | Serial | 1427 | ||
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| Author | Jose Manuel Alvarez; Felipe Lumbreras; Theo Gevers; Antonio Lopez | ||||
| Title | Geographic Information for vision-based Road Detection | Type | Conference Article | ||
| Year | 2010 | Publication | IEEE Intelligent Vehicles Symposium | Abbreviated Journal | |
| Volume | Issue | Pages | 621–626 | ||
| Keywords | road detection | ||||
| Abstract | Road detection is a vital task for the development of autonomous vehicles. The knowledge of the free road surface ahead of the target vehicle can be used for autonomous driving, road departure warning, as well as to support advanced driver assistance systems like vehicle or pedestrian detection. Using vision to detect the road has several advantages in front of other sensors: richness of features, easy integration, low cost or low power consumption. Common vision-based road detection approaches use low-level features (such as color or texture) as visual cues to group pixels exhibiting similar properties. However, it is difficult to foresee a perfect clustering algorithm since roads are in outdoor scenarios being imaged from a mobile platform. In this paper, we propose a novel high-level approach to vision-based road detection based on geographical information. The key idea of the algorithm is exploiting geographical information to provide a rough detection of the road. Then, this segmentation is refined at low-level using color information to provide the final result. The results presented show the validity of our approach. | ||||
| Address | San Diego; CA; USA | ||||
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| Area | Expedition | Conference | IV | ||
| Notes | ADAS;ISE | Approved | no | ||
| Call Number | ADAS @ adas @ ALG2010 | Serial | 1428 | ||
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| Author | Jaume Amores; David Geronimo; Antonio Lopez | ||||
| Title | Multiple instance and active learning for weakly-supervised object-class segmentation | Type | Conference Article | ||
| Year | 2010 | Publication | 3rd IEEE International Conference on Machine Vision | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Multiple Instance Learning; Active Learning; Object-class segmentation. | ||||
| Abstract | In object-class segmentation, one of the most tedious tasks is to manually segment many object examples in order to learn a model of the object category. Yet, there has been little research on reducing the degree of manual annotation for
object-class segmentation. In this work we explore alternative strategies which do not require full manual segmentation of the object in the training set. In particular, we study the use of bounding boxes as a coarser and much cheaper form of segmentation and we perform a comparative study of several Multiple-Instance Learning techniques that allow to obtain a model with this type of weak annotation. We show that some of these methods can be competitive, when used with coarse segmentations, with methods that require full manual segmentation of the objects. Furthermore, we show how to use active learning combined with this weakly supervised strategy. As we see, this strategy permits to reduce the amount of annotation and optimize the number of examples that require full manual segmentation in the training set. |
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| Address | Hong-Kong | ||||
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| Area | Expedition | Conference | ICMV | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ AGL2010b | Serial | 1429 | ||
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| Author | Joan Serrat; Antonio Lopez | ||||
| Title | Deteccion automatica de lineas de carril para la asistencia a la conduccion | Type | Miscellaneous | ||
| Year | 2010 | Publication | UAB Divulga – Revista de divulgacion cientifica | Abbreviated Journal | |
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| Abstract | La detección por cámara de las líneas de carril en las carreteras puede ser una solución asequible a los riesgos de conducción generados por los adelantamientos o las salidas de carril. Este trabajo propone un sistema que funciona en tiempo real y que obtiene muy buenos resultados. El sistema está preparado para identificar las líneas en condiciones de visibilidad poco favorables, como puede ser la conducción nocturna o con otros vehículos que dificulten la visión. | ||||
| Address | Bellaterra (Spain) | ||||
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ SeL2010 | Serial | 1430 | ||
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| Author | Marçal Rusiñol; Josep Llados | ||||
| Title | Efficient Logo Retrieval Through Hashing Shape Context Descriptors | Type | Conference Article | ||
| Year | 2010 | Publication | 9th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
| Volume | Issue | 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. | ||||
| Address | Boston; USA | ||||
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| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RuL2010b | Serial | 1434 | ||
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| Author | Herve Locteau; Sebastien Mace; Ernest Valveny; Salvatore Tabbone | ||||
| Title | Extraction des pieces de un plan de habitation | Type | Conference Article | ||
| Year | 2010 | Publication | Colloque Internacional Francophone de l´Ecrit et le Document | Abbreviated Journal | |
| Volume | Issue | 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. | ||||
| Address | Sousse, Tunisia | ||||
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| Area | Expedition | Conference | CIFED | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ LMV2010 | Serial | 1440 | ||
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| Author | Carlo Gatta; Simone Balocco; Francesco Ciompi; R. Hemetsberger; Oriol Rodriguez-Leor; Petia Radeva | ||||
| Title | Real-time gating of IVUS sequences based on motion blur analysis: Method and quantitative validation | Type | Conference Article | ||
| Year | 2010 | Publication | 13th international conference on Medical image computing and computer-assisted intervention | Abbreviated Journal | |
| Volume | II | Issue | Pages | 59-67 | |
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| Abstract | 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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| Publisher | Springer-Verlag Berlin | Place of Publication | Editor | ||
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| Area | Expedition | Conference | MICCAI | ||
| Notes | MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ GBC2010 | Serial | 1447 | ||
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| Author | Xavier Otazu; C. Alejandro Parraga; Maria Vanrell | ||||
| Title | Towards a unified chromatic inducction model | Type | Journal Article | ||
| Year | 2010 | Publication | Journal of Vision | Abbreviated Journal | VSS |
| Volume | 10 | Issue | 12:5 | Pages | 1-24 |
| Keywords | Visual system; Color induction; Wavelet transform | ||||
| Abstract | In a previous work (X. Otazu, M. Vanrell, & C. A. Párraga, 2008b), we showed how several brightness induction effects can be predicted using a simple multiresolution wavelet model (BIWaM). Here we present a new model for chromatic induction processes (termed Chromatic Induction Wavelet Model or CIWaM), which is also implemented on a multiresolution framework and based on similar assumptions related to the spatial frequency and the contrast surround energy of the stimulus. The CIWaM can be interpreted as a very simple extension of the BIWaM to the chromatic channels, which in our case are defined in the MacLeod-Boynton (lsY) color space. This new model allows us to unify both chromatic assimilation and chromatic contrast effects in a single mathematical formulation. The predictions of the CIWaM were tested by means of several color and brightness induction experiments, which showed an acceptable agreement between model predictions and psychophysical data. | ||||
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ OPV2010 | Serial | 1450 | ||
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| Author | Jose Manuel Alvarez; Theo Gevers; Antonio Lopez | ||||
| Title | Learning photometric invariance for object detection | Type | Journal Article | ||
| Year | 2010 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
| Volume | 90 | Issue | 1 | Pages | 45-61 |
| Keywords | road detection | ||||
| Abstract | Impact factor: 3.508 (the last available from JCR2009SCI). Position 4/103 in the category Computer Science, Artificial Intelligence. Quartile
Color is a powerful visual cue in many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the imaging conditions that negatively affect the performance of the task at hand. Often, a reflection model (e.g., Lambertian or dichromatic reflectance) is used to derive color invariant models. However, this approach may be too restricted to model real-world scenes in which different reflectance mechanisms can hold simultaneously. Therefore, in this paper, we aim to derive color invariance by learning from color models to obtain diversified color invariant ensembles. First, a photometrical orthogonal and non-redundant color model set is computed composed of both color variants and invariants. Then, the proposed method combines these color models to arrive at a diversified color ensemble yielding a proper balance between invariance (repeatability) and discriminative power (distinctiveness). To achieve this, our fusion method uses a multi-view approach to minimize the estimation error. In this way, the proposed method is robust to data uncertainty and produces properly diversified color invariant ensembles. Further, the proposed method is extended to deal with temporal data by predicting the evolution of observations over time. Experiments are conducted on three different image datasets to validate the proposed method. Both the theoretical and experimental results show that the method is robust against severe variations in imaging conditions. The method is not restricted to a certain reflection model or parameter tuning, and outperforms state-of-the-art detection techniques in the field of object, skin and road recognition. Considering sequential data, the proposed method (extended to deal with future observations) outperforms the other methods |
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| Publisher | Springer US | Place of Publication | Editor | ||
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| ISSN | 0920-5691 | ISBN |
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| Notes | ADAS;ISE | Approved | no | ||
| Call Number | ADAS @ adas @ AGL2010c | Serial | 1451 | ||
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| Author | Sergio Escalera; Oriol Pujol; Eric Laciar; Jordi Vitria; Esther Pueyo; Petia Radeva | ||||
| Title | Classification of Coronary Damage in Chronic Chagasic Patients | Type | Book Chapter | ||
| Year | 2010 | Publication | Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence | Abbreviated Journal | |
| Volume | 299 | Issue | Pages | 461-478 | |
| Keywords | Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding | ||||
| 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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| Publisher | Springer-Verlag | Place of Publication | Editor | V. Sgurev, M. Hadjiski (eds) | |
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| Notes | OR;MILAB;HUPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPL2010 | Serial | 1452 | ||
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| Author | Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva | ||||
| Title | Conditional Random Fields for image segmentation in Intravascular Ultrasound | Type | Conference Article | ||
| Year | 2010 | Publication | Medical Image Computing in Catalunya: Graduate Student Workshop | Abbreviated Journal | |
| Volume | Issue | 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. | ||||
| Address | Girona | ||||
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| Area | Expedition | Conference | MICCAT | ||
| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPF2010 | Serial | 1453 | ||
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| Author | Ariel Amato; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez | ||||
| Title | Robust Real-Time Background Subtraction Based on Local Neighborhood Patterns | Type | Journal Article | ||
| Year | 2010 | Publication | EURASIP Journal on Advances in Signal Processing | Abbreviated Journal | EURASIPJ |
| Volume | Issue | Pages | 7 | ||
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| Abstract | Article ID 901205
This paper describes an efficient background subtraction technique for detecting moving objects. The proposed approach is able to overcome difficulties like illumination changes and moving shadows. Our method introduces two discriminative features based on angular and modular patterns, which are formed by similarity measurement between two sets of RGB color vectors: one belonging to the background image and the other to the current image. We show how these patterns are used to improve foreground detection in the presence of moving shadows and in the case when there are strong similarities in color between background and foreground pixels. Experimental results over a collection of public and own datasets of real image sequences demonstrate that the proposed technique achieves a superior performance compared with state-of-the-art methods. Furthermore, both the low computational and space complexities make the presented algorithm feasible for real-time applications. |
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| ISSN | 1110-8657 | ISBN |
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| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ AMR2010 | Serial | 1463 | ||
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| Author | Pierluigi Casale; Oriol Pujol; Petia Radeva | ||||
| Title | Embedding Random Projections in Regularized Gradient Boosting Machines | Type | Conference Article | ||
| Year | 2010 | Publication | Supervised and Unsupervised Ensemble Methods and their Applications in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases | Abbreviated Journal | |
| Volume | Issue | Pages | 44–53 | ||
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| Address | Barcelona (Spain) | ||||
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| Area | Expedition | Conference | SUEMA | ||
| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPR2010c | Serial | 1466 | ||
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| Author | Pierluigi Casale; Oriol Pujol; Petia Radeva | ||||
| Title | Classyfing Agitation in Sedated ICU Patients | Type | Conference Article | ||
| Year | 2010 | Publication | Medical Image Computing in Catalunya: Graduate Student Workshop | Abbreviated Journal | |
| Volume | Issue | Pages | 19–20 | ||
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| Abstract | Agitation is a serious problem in sedated intensive care unit (ICU) patients. In this work, standard machine learning techniques working on wearable accelerometer data have been used to classifying agitation levels achieving very good classification performances. | ||||
| Address | Girona | ||||
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| Area | Expedition | Conference | MICCAT | ||
| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ COR2010 | Serial | 1467 | ||
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| Author | Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
| Title | Reduction of Pattern Search Area in Colonoscopy Images by Merging Non-Informative Regions | Type | Conference Article | ||
| Year | 2010 | Publication | 28th Congreso Anual de la Sociedad Española de Ingeniería Biomédica | Abbreviated Journal | |
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| Abstract | One of the first usual steps in pattern recognition schemas is image segmentation, in order to reduce the dimensionality of the problem and manage smaller quantity of data. In our case as we are pursuing real-time colon cancer polyp detection, this step is crucial. In this paper we present a non-informative region estimation algorithm that will let us discard some parts of the image where we will not expect to find colon cancer polyps. The performance of our approach will be measured in terms of both non-informative areas elimination and polyps’ areas preserving. The results obtained show the importance of having correct non- informative region estimation in order to fasten the whole recognition process. | ||||
| Address | Madrid (Spain) | ||||
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| Area | 800 | Expedition | Conference | CASEIB | |
| Notes | MV;SIAI | Approved | no | ||
| Call Number | Admin @ si @ BSV2010 | Serial | 1469 | ||
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