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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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| Author | J. Chazalon; Marçal Rusiñol; Jean-Marc Ogier | ||||
| Title | Improving Document Matching Performance by Local Descriptor Filtering | Type | Conference Article | ||
| Year | 2015 | Publication | 6th IAPR International Workshop on Camera Based Document Analysis and Recognition CBDAR2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 1216 - 1220 | ||
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| Abstract | In this paper we propose an effective method aimed at reducing the amount of local descriptors to be indexed in a document matching framework. In an off-line training stage, the matching between the model document and incoming images is computed retaining the local descriptors from the model that steadily produce good matches. We have evaluated this approach by using the ICDAR2015 SmartDOC dataset containing near 25 000 images from documents to be captured by a mobile device. We have tested the performance of this filtering step by using
ORB and SIFT local detectors and descriptors. The results show an important gain both in quality of the final matching as well as in time and space requirements. |
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| Address | Nancy; France; August 2015 | ||||
| Corporate Author | Thesis | ||||
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| Language | Summary Language | Original Title | |||
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| Area | Expedition | Conference |
CBDAR | ||
| Notes | DAG; 600.077; 601.223; 600.084 | Approved | no | ||
| Call Number | Admin @ si @ CRO2015a | Serial | 2680 | ||
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| Author | Suman Ghosh; Lluis Gomez; Dimosthenis Karatzas; Ernest Valveny | ||||
| Title | Efficient indexing for Query By String text retrieval | Type | Conference Article | ||
| Year | 2015 | Publication | 6th IAPR International Workshop on Camera Based Document Analysis and Recognition CBDAR2015 | Abbreviated Journal | |
| Volume | Issue | Pages | 1236 - 1240 | ||
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| Abstract | This paper deals with Query By String word spotting in scene images. A hierarchical text segmentation algorithm based on text specific selective search is used to find text regions. These regions are indexed per character n-grams present in the text region. An attribute representation based on Pyramidal Histogram of Characters (PHOC) is used to compare text regions with the query text. For generation of the index a similar attribute space based Pyramidal Histogram of character n-grams is used. These attribute models are learned using linear SVMs over the Fisher Vector [1] representation of the images along with the PHOC labels of the corresponding strings. | ||||
| Address | Nancy; France; August 2015 | ||||
| Corporate Author | Thesis | ||||
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| Series Editor | Series Title | Abbreviated Series Title | |||
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| Area | Expedition | Conference |
CBDAR | ||
| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ GGK2015 | Serial | 2693 | ||
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| Author | Ahmed M. A. Salih; Ilaria Boscolo Galazzo; Zahra Zahra Raisi-Estabragh; Steffen E. Petersen; Polyxeni Gkontra; Karim Lekadir; Gloria Menegaz; Petia Radeva | ||||
| Title | A new scheme for the assessment of the robustness of Explainable Methods Applied to Brain Age estimation | Type | Conference Article | ||
| Year | 2021 | Publication | 34th International Symposium on Computer-Based Medical Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 492-497 | ||
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| Abstract | Deep learning methods show great promise in a range of settings including the biomedical field. Explainability of these models is important in these fields for building end-user trust and to facilitate their confident deployment. Although several Machine Learning Interpretability tools have been proposed so far, there is currently no recognized evaluation standard to transfer the explainability results into a quantitative score. Several measures have been proposed as proxies for quantitative assessment of explainability methods. However, the robustness of the list of significant features provided by the explainability methods has not been addressed. In this work, we propose a new proxy for assessing the robustness of the list of significant features provided by two explainability methods. Our validation is defined at functionality-grounded level based on the ranked correlation statistical index and demonstrates its successful application in the framework of brain aging estimation. We assessed our proxy to estimate brain age using neuroscience data. Our results indicate small variability and high robustness in the considered explainability methods using this new proxy. | ||||
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| Area | Expedition | Conference |
CBMS | ||
| Notes | MILAB; no proj | Approved | no | ||
| Call Number | Admin @ si @ SBZ2021 | Serial | 3629 | ||
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| Author | Fernando Vilariño; Petia Radeva | ||||
| Title | Cardiac Segmentation with Discriminant Active Contours | Type | Book Chapter | ||
| Year | 2003 | Publication | Abbreviated Journal | ||
| Volume | Issue | Pages | 211–217 | ||
| Keywords | |||||
| Abstract | Dynamic tracking of heart moving is one relevant target in medical imag- ing and can be helpful for analyzing heart dynamics in the study of several cardiac diseases. For this aim, a previous segmentation problem of such structures is stated, based on certain relevant features (like edges or intensity levels, textures, etc.) Clas- sical active models have been used, but they fail when overlapping structures or not well-defined contours are present. Automatic feature learning systems may be a pow- erful tool. Discriminant active contours present optimal results in this kind of problem. They are a kind of deformable models that converge to an optimal object segmenta- tion that dynamically adapts to the object contour. The feature space is designed from a filter bank in order to guarantee the search and learning of the set of relevant fea- tures for optimal classification on each part of the object. Tracking of target evolution is obtained through the whole set of images, using information from the actual and previous stages. Feedback systems are implemented to guarantee the minimum well- separable classification set in each segmentation step. Our implementation has been proved with several series of Magnetic Resonance with improved results in segmenta- tion in comparison to previous methods. | ||||
| Address | Palma de Mallorca | ||||
| Corporate Author | Thesis | ||||
| Publisher | IOS Press | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference |
CCIA | ||
| Notes | MV;MILAB;SIAI | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ ViR2003; IAM @ iam @ VRa2003 | Serial | 426 | ||
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| Author | Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva | ||||
| Title | Text Detection in Urban Scenes (video sample) | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 35–44 | |
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| Abstract | Abstract. Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are just a few problems. Text detection can be specially suited for georeferencing business, navigation, tourist assistance, or to help visual impaired people. In this paper, we propose a general methodology to deal with the problem of text detection in outdoor scenes. The method is based on learning spatial information of gradient based features and Census Transform images using a cascade of classifiers. The method is applied in the context of Mobile Mapping systems, where a mobile vehicle captures urban image sequences. Moreover, a cover data set is presented and tested with the new methodology. The results show high accuracy when detecting multi-linear text regions with high variability of appearance, at same time that it preserves a low false alarm rate compared to classical approaches | ||||
| Address | Cardona (Spain) | ||||
| Corporate Author | Thesis | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference |
CCIA | ||
| Notes | OR;MILAB;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EBV2009 | Serial | 1181 | ||
| Permanent link to this record | |||||
| Author | Sergio Escalera; Oriol Pujol; Petia Radeva; Jordi Vitria | ||||
| Title | Measuring Interest of Human Dyadic Interactions | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 45-54 | |
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| Abstract | In this paper, we argue that only using behavioural motion information, we are able to predict the interest of observers when looking at face-to-face interactions. We propose a set of movement-related features from body, face, and mouth activity in order to define a set of higher level interaction features, such as stress, activity, speaking engagement, and corporal engagement. Error-Correcting Output Codes framework with an Adaboost base classifier is used to learn to rank the perceived observer's interest in face-to-face interactions. The automatic system shows good correlation between the automatic categorization results and the manual ranking made by the observers. In particular, the learning system shows that stress features have a high predictive power for ranking interest of observers when looking at of face-to-face interactions. | ||||
| Address | Cardona (Spain) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference |
CCIA | ||
| Notes | OR;MILAB;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPR2009b | Serial | 1182 | ||
| Permanent link to this record | |||||
| Author | Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria | ||||
| Title | Generic Object Recognition in Urban Image Databases | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 27-34 | |
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| Abstract | In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (>500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. All this information is extracted without an object of reference, which allows to search for any type of objects using their visual appearance. A new Visual Content layer is built over Google Maps, allowing the object recognition information to be organized and fused with other content, like satellite images, street maps, and business locations. | ||||
| Address | Cardona (Spain) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference |
CCIA | ||
| Notes | OR;MILAB;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ VER2009 | Serial | 1183 | ||
| Permanent link to this record | |||||
| Author | Francesco Ciompi; Oriol Pujol; Oriol Rodriguez-Leor; Angel Serrano; J. Mauri; Petia Radeva | ||||
| Title | On in-vitro and in-vivo IVUS data fusion | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 147-156 | |
| Keywords | |||||
| Abstract | The design and the validation of an automatic plaque characterization technique based on Intravascular Ultrasound (IVUS) usually requires a data ground-truth. The histological analysis of post-mortem coronary arteries is commonly assumed as the state-of-the-art process for the extraction of a reliable data-set of atherosclerotic plaques. Unfortunately, the amount of data provided by this technique is usually few, due to the difficulties in collecting post-mortem cases and phenomena of tissue spoiling during histological analysis. In this paper we tackle the process of fusing in-vivo and in-vitro IVUS data starting with the analysis of recently proposed approaches for the creation of an enhanced IVUS data-set; furthermore, we propose a new approach, named pLDS, based on semi-supervised learning with a data selection criterion. The enhanced data-set obtained by each one of the analyzed approaches is used to train a classifier for tissue characterization purposes. Finally, the discriminative power of each classifier is quantitatively assessed and compared by classifying a data-set of validated in-vitro IVUS data. | ||||
| Address | Cardona (Spain) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference |
CCIA | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPR2009d | Serial | 1204 | ||
| Permanent link to this record | |||||
| Author | Pierluigi Casale; Oriol Pujol; Petia Radeva; Jordi Vitria | ||||
| Title | A First Approach to Activity Recognition Using Topic Models | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 74 - 82 | |
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| Abstract | In this work, we present a first approach to activity patterns discovery by mean of topic models. Using motion data collected with a wearable device we prototype, TheBadge, we analyse raw accelerometer data using Latent Dirichlet Allocation (LDA), a particular instantiation of topic models. Results show that for particular values of the parameters necessary for applying LDA to a countinous dataset, good accuracies in activity classification can be achieved. | ||||
| Address | Cardona, Spain | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference |
CCIA | ||
| Notes | OR;MILAB;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPR2009e | Serial | 1231 | ||
| Permanent link to this record | |||||
| Author | Arnau Ramisa; Shrihari Vasudevan; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras | ||||
| Title | Evaluation of the SIFT Object Recognition Method in Mobile Robots: Frontiers in Artificial Intelligence and Applications | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 9-18 | |
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| Abstract | General object recognition in mobile robots is of primary importance in order to enhance the representation of the environment that robots will use for their reasoning processes. Therefore, we contribute reduce this gap by evaluating the SIFT Object Recognition method in a challenging dataset, focusing on issues relevant to mobile robotics. Resistance of the method to the robotics working conditions was found, but it was limited mainly to well-textured objects. | ||||
| Address | Cardona, Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0922-6389 | ISBN | 978-1-60750-061-2 | Medium | |
| Area | Expedition | Conference |
CCIA | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ RVA2009 | Serial | 1248 | ||
| Permanent link to this record | |||||
| Author | David Aldavert; Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo | ||||
| Title | Real-time Object Segmentation using a Bag of Features Approach | Type | Conference Article | ||
| Year | 2010 | Publication | 13th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 220 | Issue | Pages | 321–329 | |
| Keywords | Object Segmentation; Bag Of Features; Feature Quantization; Densely sampled descriptors | ||||
| Abstract | In this paper, we propose an object segmentation framework, based on the popular bag of features (BoF), which can process several images per second while achieving a good segmentation accuracy assigning an object category to every pixel of the image. We propose an efficient color descriptor to complement the information obtained by a typical gradient-based local descriptor. Results show that color proves to be a useful cue to increase the segmentation accuracy, specially in large homogeneous regions. Then, we extend the Hierarchical K-Means codebook using the recently proposed Vector of Locally Aggregated Descriptors method. Finally, we show that the BoF method can be easily parallelized since it is applied locally, thus the time necessary to process an image is further reduced. The performance of the proposed method is evaluated in the standard PASCAL 2007 Segmentation Challenge object segmentation dataset. | ||||
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| Publisher | IOS Press Amsterdam, | Place of Publication | Editor | In R.Alquezar, A.Moreno, J.Aguilar. | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 9781607506423 | Medium | ||
| Area | Expedition | Conference |
CCIA | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ ARL2010b | Serial | 1417 | ||
| Permanent link to this record | |||||
| Author | Eloi Puertas; Sergio Escalera; Oriol Pujol | ||||
| Title | Classifying Objects at Different Sizes with Multi-Scale Stacked Sequential Learning | Type | Conference Article | ||
| Year | 2010 | Publication | 13th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 220 | Issue | Pages | 193–200 | |
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| Abstract | Sequential learning is that discipline of machine learning that deals with dependent data. In this paper, we use the Multi-scale Stacked Sequential Learning approach (MSSL) to solve the task of pixel-wise classification based on contextual information. The main contribution of this work is a shifting technique applied during the testing phase that makes possible, thanks to template images, to classify objects at different sizes. The results show that the proposed method robustly classifies such objects capturing their spatial relationships. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | R. Alquezar, A. Moreno, J. Aguilar | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60750-642-3 | Medium | ||
| Area | Expedition | Conference |
CCIA | ||
| Notes | HUPBA;MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PEP2010 | Serial | 1448 | ||
| Permanent link to this record | |||||
| Author | Jaume Garcia; Petia Radeva; Francesc Carreras | ||||
| Title | Combining Spectral and Active Shape methods to Track Tagged MRI | Type | Book Chapter | ||
| Year | 2004 | Publication | Recent Advances in Artificial Intelligence Research and Development | Abbreviated Journal | |
| Volume | Issue | Pages | 37-44 | ||
| Keywords | MR; tagged MR; ASM; LV segmentation; motion estimation. | ||||
| Abstract | Tagged magnetic resonance is a very usefull and unique tool that provides a complete local and global knowledge of the left ventricle (LV) motion. In this article we introduce a method capable of tracking and segmenting the LV. Spectral methods are applied in order to obtain the so called HARP images which encode information about movement and are the base for LV point-tracking. For segmentation we use Active Shapes (ASM) that model LV shape variation in order to overcome possible local misplacements of the boundary. We finally show experiments on both synthetic and real data which appear to be very promising. | ||||
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| Publisher | IOS Press | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference |
CCIA | ||
| Notes | IAM;MILAB | Approved | no | ||
| Call Number | IAM @ iam @ GRC2004 | Serial | 1488 | ||
| Permanent link to this record | |||||
| Author | David Roche; Debora Gil; Jesus Giraldo | ||||
| Title | An inference model for analyzing termination conditions of Evolutionary Algorithms | Type | Conference Article | ||
| Year | 2011 | Publication | 14th Congrès Català en Intel·ligencia Artificial | Abbreviated Journal | |
| Volume | Issue | Pages | 216-225 | ||
| Keywords | Evolutionary Computation Convergence, Termination Conditions, Statistical Inference | ||||
| Abstract | In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used.
We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution. |
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| Address | Lleida, Catalonia (Spain) | ||||
| Corporate Author | Associació Catalana Intel·ligència Artificial | Thesis | |||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-60750-841-0 | Medium | ||
| Area | Expedition | Conference |
CCIA | ||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ RGG2011a | Serial | 1677 | ||
| Permanent link to this record | |||||