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| 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 | ||||
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| 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 | ||
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| Author | Carlo Gatta; Oriol Pujol; O. Rodriguez-Leor; J. M. Ferre; Petia Radeva | ||||
| Title | Fast Rigid Registration of Vascular Structures in IVUS Sequences | Type | Journal Article | ||
| Year | 2009 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | |
| Volume | 13 | Issue | 6 | Pages | 106-1011 |
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| Abstract | Intravascular ultrasound (IVUS) technology permits visualization of high-resolution images of internal vascular structures. IVUS is a unique image-guiding tool to display longitudinal view of the vessels, and estimate the length and size of vascular structures with the goal of accurate diagnosis. Unfortunately, due to pulsatile contraction and expansion of the heart, the captured images are affected by different motion artifacts that make visual inspection difficult. In this paper, we propose an efficient algorithm that aligns vascular structures and strongly reduces the saw-shaped oscillation, simplifying the inspection of longitudinal cuts; it reduces the motion artifacts caused by the displacement of the catheter in the short-axis plane and the catheter rotation due to vessel tortuosity. The algorithm prototype aligns 3.16 frames/s and clearly outperforms state-of-the-art methods with similar computational cost. The speed of the algorithm is crucial since it allows to inspect the corrected sequence during patient intervention. Moreover, we improved an indirect methodology for IVUS rigid registration algorithm evaluation. | ||||
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| ISSN | 1089-7771 | ISBN | Medium | ||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ GPL2009 | Serial | 1250 | ||
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| Author | Fosca De Iorio; C. Malagelada; Fernando Azpiroz; M. Maluenda; C. Violanti; Laura Igual; Jordi Vitria; Juan R. Malagelada | ||||
| Title | Intestinal motor activity, endoluminal motion and transit | Type | Journal Article | ||
| Year | 2009 | Publication | Neurogastroenterology & Motility | Abbreviated Journal | NEUMOT |
| Volume | 21 | Issue | 12 | Pages | 1264–e119 |
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| Abstract | A programme for evaluation of intestinal motility has been recently developed based on endoluminal image analysis using computer vision methodology and machine learning techniques. Our aim was to determine the effect of intestinal muscle inhibition on wall motion, dynamics of luminal content and transit in the small bowel. Fourteen healthy subjects ingested the endoscopic capsule (Pillcam, Given Imaging) in fasting conditions. Seven of them received glucagon (4.8 microg kg(-1) bolus followed by a 9.6 microg kg(-1) h(-1) infusion during 1 h) and in the other seven, fasting activity was recorded, as controls. This dose of glucagon has previously shown to inhibit both tonic and phasic intestinal motor activity. Endoluminal image and displacement was analyzed by means of a computer vision programme specifically developed for the evaluation of muscular activity (contractile and non-contractile patterns), intestinal contents, endoluminal motion and transit. Thirty-minute periods before, during and after glucagon infusion were analyzed and compared with equivalent periods in controls. No differences were found in the parameters measured during the baseline (pretest) periods when comparing glucagon and control experiments. During glucagon infusion, there was a significant reduction in contractile activity (0.2 +/- 0.1 vs 4.2 +/- 0.9 luminal closures per min, P < 0.05; 0.4 +/- 0.1 vs 3.4 +/- 1.2% of images with radial wrinkles, P < 0.05) and a significant reduction of endoluminal motion (82 +/- 9 vs 21 +/- 10% of static images, P < 0.05). Endoluminal image analysis, by means of computer vision and machine learning techniques, can reliably detect reduced intestinal muscle activity and motion. | ||||
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| Notes | OR;MILAB;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ DMA2009 | Serial | 1251 | ||
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| Author | Oriol Pujol; David Masip | ||||
| Title | Geometry-Based Ensembles: Toward a Structural Characterization of the Classification Boundary | Type | Journal Article | ||
| Year | 2009 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 31 | Issue | 6 | Pages | 1140–1146 |
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| Abstract | This article introduces a novel binary discriminative learning technique based on the approximation of the non-linear decision boundary by a piece-wise linear smooth additive model. The decision border is geometrically defined by means of the characterizing boundary points – points that belong to the optimal boundary under a certain notion of robustness. Based on these points, a set of locally robust linear classifiers is defined and assembled by means of a Tikhonov regularized optimization procedure in an additive model to create a final lambda-smooth decision rule. As a result, a very simple and robust classifier with a strong geometrical meaning and non-linear behavior is obtained. The simplicity of the method allows its extension to cope with some of nowadays machine learning challenges, such as online learning, large scale learning or parallelization, with linear computational complexity. We validate our approach on the UCI database. Finally, we apply our technique in online and large scale scenarios, and in six real life computer vision and pattern recognition problems: gender recognition, intravascular ultrasound tissue classification, speed traffic sign detection, Chagas' disease severity detection, clef classification and action recognition using a 3D accelerometer data. The results are promising and this paper opens a line of research that deserves further attention | ||||
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| Notes | OR;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PuM2009 | Serial | 1252 | ||
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| Author | J. Oliver; Ricardo Toledo; J. Pujol; J. Sorribes; E. Valderrama | ||||
| Title | Un ABP basado en la robotica para las ingenierias informaticas | Type | Miscellaneous | ||
| Year | 2009 | Publication | 15th Jornadas de Enseñanza Universitaria de la Informatica | Abbreviated Journal | |
| Volume | Issue | Pages | 331–338 | ||
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| Address | Barcelona, Spain | ||||
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| ISSN | ISBN | ISBN:978–84–692–2758–9 | Medium | ||
| Area | Expedition | Conference | JENUI | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ OTP2009 | Serial | 1253 | ||
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| Author | Eduard Vazquez | ||||
| Title | Distribution Characterization using Topological Features. Application to Colour Image Processing | Type | Report | ||
| Year | 2007 | Publication | CVC Technical Report # 107 | Abbreviated Journal | |
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| Corporate Author | Thesis | Master's thesis | |||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Vaz2009 | Serial | 1254 | ||
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| Author | Oscar Camara; Estanislao Oubel; Gemma Piella; Simone Balocco; Mathieu De Craene; Alejandro F. Frangi | ||||
| Title | Multi-sequence Registration of Cine, Tagged and Delay-Enhancement MRI with Shift Correction and Steerable Pyramid-Based Detagging | Type | Conference Article | ||
| Year | 2009 | Publication | 5th International Conference on Functional Imaging and Modeling of the Heart | Abbreviated Journal | |
| Volume | 5528 | Issue | Pages | 330–338 | |
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| Abstract | In this work, we present a registration framework for cardiac cine MRI (cMRI), tagged (tMRI) and delay-enhancement MRI (deMRI), where the two main issues to find an accurate alignment between these images have been taking into account: the presence of tags in tMRI and respiration artifacts in all sequences. A steerable pyramid image decomposition has been used for detagging purposes since it is suitable to extract high-order oriented structures by directional adaptive filtering. Shift correction of cMRI is achieved by firstly maximizing the similarity between the Long Axis and Short Axis cMRI. Subsequently, these shift-corrected images are used as target images in a rigid registration procedure with their corresponding tMRI/deMRI in order to correct their shift. The proposed registration framework has been evaluated by 840 registration tests, considerably improving the alignment of the MR images (mean RMS error of 2.04mm vs. 5.44mm). | ||||
| Address | Nice, France | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| ISSN | 0302-9743 | ISBN | 978-3-642-01931-9 | Medium | |
| Area | Expedition | Conference | FIMH | ||
| Notes | MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ COP2009 | Serial | 1255 | ||
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| Author | Fadi Dornaika; Bogdan Raducanu | ||||
| Title | Simultaneous 3D face pose and person-specific shape estimation from a single image using a holistic approach | Type | Conference Article | ||
| Year | 2009 | Publication | IEEE Workshop on Applications of Computer Vision | Abbreviated Journal | |
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| Abstract | This paper presents a new approach for the simultaneous estimation of the 3D pose and specific shape of a previously unseen face from a single image. The face pose is not limited to a frontal view. We describe a holistic approach based on a deformable 3D model and a learned statistical facial texture model. Rather than obtaining a person-specific facial surface, the goal of this work is to compute person-specific 3D face shape in terms of a few control parameters that are used by many applications. The proposed holistic approach estimates the 3D pose parameters as well as the face shape control parameters by registering the warped texture to a statistical face texture, which is carried out by a stochastic and genetic optimizer. The proposed approach has several features that make it very attractive: (i) it uses a single grey-scale image, (ii) it is person-independent, (iii) it is featureless (no facial feature extraction is required), and (iv) its learning stage is easy. The proposed approach lends itself nicely to 3D face tracking and face gesture recognition in monocular videos. We describe extensive experiments that show the feasibility and robustness of the proposed approach. | ||||
| Address | Utah, USA | ||||
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| ISSN | 1550-5790 | ISBN | 978-1-4244-5497-6 | Medium | |
| Area | Expedition | Conference | WACV | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ DoR2009b | Serial | 1256 | ||
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| Author | Bogdan Raducanu; Fadi Dornaika | ||||
| Title | Natural Facial Expression Recognition Using Dynamic and Static Schemes | Type | Conference Article | ||
| Year | 2009 | Publication | 5th International Symposium on Visual Computing | Abbreviated Journal | |
| Volume | 5875 | Issue | Pages | 730–739 | |
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| Abstract | Affective computing is at the core of a new paradigm in HCI and AI represented by human-centered computing. Within this paradigm, it is expected that machines will be enabled with perceiving capabilities, making them aware about users’ affective state. The current paper addresses the problem of facial expression recognition from monocular videos sequences. We propose a dynamic facial expression recognition scheme, which is proven to be very efficient. Furthermore, it is conveniently compared with several static-based systems adopting different magnitude of facial expression. We provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). We also provide performance evaluations using arbitrary test video sequences. | ||||
| Address | Las Vegas, USA | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| ISSN | 0302-9743 | ISBN | 978-3-642-10330-8 | Medium | |
| Area | Expedition | Conference | ISVC | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RaD2009 | Serial | 1257 | ||
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| Author | Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva | ||||
| Title | Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes | Type | Journal Article | ||
| Year | 2009 | Publication | Journal of Signal Processing Systems | Abbreviated Journal | |
| Volume | 55 | Issue | 1-3 | Pages | 35–47 |
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| Abstract | Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches. | ||||
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| ISSN | 1939-8018 | ISBN | Medium | ||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPM2009 | Serial | 1258 | ||
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| Author | Anjan Dutta; Zeynep Akata | ||||
| Title | Semantically Tied Paired Cycle Consistency for Zero-Shot Sketch-based Image Retrieval | Type | Conference Article | ||
| Year | 2019 | Publication | 32nd IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 5089-5098 | ||
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| Abstract | Zero-shot sketch-based image retrieval (SBIR) is an emerging task in computer vision, allowing to retrieve natural images relevant to sketch queries that might not been seen in the training phase. Existing works either require aligned sketch-image pairs or inefficient memory fusion layer for mapping the visual information to a semantic space. In this work, we propose a semantically aligned paired cycle-consistent generative (SEM-PCYC) model for zero-shot SBIR, where each branch maps the visual information to a common semantic space via an adversarial training. Each of these branches maintains a cycle consistency that only requires supervision at category levels, and avoids the need of highly-priced aligned sketch-image pairs. A classification criteria on the generators' outputs ensures the visual to semantic space mapping to be discriminating. Furthermore, we propose to combine textual and hierarchical side information via a feature selection auto-encoder that selects discriminating side information within a same end-to-end model. Our results demonstrate a significant boost in zero-shot SBIR performance over the state-of-the-art on the challenging Sketchy and TU-Berlin datasets. | ||||
| Address | Long beach; California; USA; June 2019 | ||||
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| Area | Expedition | Conference | CVPR | ||
| Notes | DAG; 600.141; 600.121 | Approved | no | ||
| Call Number | Admin @ si @ DuA2019 | Serial | 3268 | ||
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| Author | Oriol Pujol; Eloi Puertas; Carlo Gatta | ||||
| Title | Multi-scale Stacked Sequential Learning | Type | Conference Article | ||
| Year | 2009 | Publication | 8th International Workshop of Multiple Classifier Systems | Abbreviated Journal | |
| Volume | 5519 | Issue | Pages | 262–271 | |
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| Abstract | One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions. | ||||
| Address | Reykjavik, Iceland | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| ISSN | 0302-9743 | ISBN | 978-3-642-02325-5 | Medium | |
| Area | Expedition | Conference | MCS | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PPG2009 | Serial | 1260 | ||
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| Author | David Rotger | ||||
| Title | Analysis and Multi-Modal Fusion of coronary Images | Type | Book Whole | ||
| Year | 2009 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | The framework of this thesis is to study in detail different techniques and tools for medical image registration in order to ease the daily life of clinical experts in cardiology. The first aim of this thesis is providing computer tools for
fusing IVUS and angiogram data is of high clinical interest to help the physicians locate in IVUS data and decide which lesion is observed, how long it is, how far from a bifurcation or another lesions stays, etc. This thesis proves and validates that we can segment the catheter path in angiographies using geodesic snakes (based on fast marching algorithm), a three-dimensional reconstruction of the catheter inspired in stereo vision and a new technique to fuse IVUS and angiograms that establishes exact correspondences between them. We have developed a new workstation called iFusion that has four strong advantages: registration of IVUS and angiographic images with sub-pixel precision, it works on- and off-line, it is independent on the X-ray system and there is no need of daily calibration. The second aim of the thesis is devoted to developing a computer-aided analysis of IVUS for image-guided intervention. We have designed, implemented and validated a robust algorithm for stent extraction and reconstruction from IVUS videos. We consider a very special and recent kind of stents, bioabsorbable stents that represent a great clinical challenge due to their property to be absorbed by time and thus avoiding the “danger” of neostenosis as one of the main problems of metallic stents. We present a new and very promising algorithm based on an optimized cascade of multiple classifiers to automatically detect individual stent struts of a very novel bioabsorbable drug eluting coronary stent. This problem represents a very challenging target given the variability in contrast, shape and grey levels of the regions to be detected, what is denoted by the high variability between the specialists (inter-observer variability of 0.14~$\pm$0.12). The obtained results of the automatic strut detection are within the inter-observer variability. |
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| Address | Barcelona (Espanya) | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Petia Radeva | |
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Rot2009 | Serial | 1261 | ||
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| Author | Xavier Baro | ||||
| Title | Probabilistic Darwin Machines: A New Approach to Develop Evolutionary Object Detection | Type | Book Whole | ||
| Year | 2009 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Ever since computers were invented, we have wondered whether they might perform some of the human quotidian tasks. One of the most studied and still nowadays less understood problem is the capacity to learn from our experiences and how we generalize the knowledge that we acquire. One of that unaware tasks for the persons and that more interest is awakening in different scientific areas since the beginning, is the one that is known as pattern recognition. The creation of models that represent the world that surrounds us, help us for recognizing objects in our environment, to predict situations, to identify behaviors... All this information allows us to adapt ourselves and to interact with our environment. The capacity of adaptation of individuals to their environment has been related to the amount of patterns that are capable of identifying.
This thesis faces the pattern recognition problem from a Computer Vision point of view, taking one of the most paradigmatic and extended approaches to object detection as starting point. After studying this approach, two weak points are identified: The first makes reference to the description of the objects, and the second is a limitation of the learning algorithm, which hampers the utilization of best descriptors. In order to address the learning limitations, we introduce evolutionary computation techniques to the classical object detection approach. After testing the classical evolutionary approaches, such as genetic algorithms, we develop a new learning algorithm based on Probabilistic Darwin Machines, which better adapts to the learning problem. Once the learning limitation is avoided, we introduce a new feature set, which maintains the benefits of the classical feature set, adding the ability to describe non localities. This combination of evolutionary learning algorithm and features is tested on different public data sets, outperforming the results obtained by the classical approach. |
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| Address | Barcelona (Spain) | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Vitria | |
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| Notes | OR;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ Bar2009 | Serial | 1262 | ||
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| Author | Agata Lapedriza | ||||
| Title | Multitask Learning Techniques for Automatic Face Classification | Type | Book Whole | ||
| Year | 2009 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Automatic face classification is currently a popular research area in Computer Vision. It involves several subproblems, such as subject recognition, gender classification or subject verification.
Current systems of automatic face classification need a large amount of training data to robustly learn a task. However, the collection of labeled data is usually a difficult issue. For this reason, the research on methods that are able to learn from a small sized training set is essential. The dependency on the abundance of training data is not so evident in human learning processes. We are able to learn from a very small number of examples, given that we use, additionally, some prior knowledge to learn a new task. For example, we frequently find patterns and analogies from other domains to reuse them in new situations, or exploit training data from other experiences. In computer science, Multitask Learning is a new Machine Learning approach that studies this idea of knowledge transfer among different tasks, to overcome the effects of the small sample sized problem. This thesis explores, proposes and tests some Multitask Learning methods specially developed for face classification purposes. Moreover, it presents two more contributions dealing with the small sample sized problem, out of the Multitask Learning context. The first one is a method to extract external face features, to be used as an additional information source in automatic face classification problems. The second one is an empirical study on the most suitable face image resolution to perform automatic subject recognition. |
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| Address | Barcelona (Spain) | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Vitria;David Masip | |
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| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ Lap2009 | Serial | 1263 | ||
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