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| Author | Onur Ferhat; Fernando Vilariño; F. Javier Sanchez | ||||
| Title | A cheap portable eye-tracker solution for common setups. | Type | Journal Article | ||
| Year | 2014 | Publication | Journal of Eye Movement Research | Abbreviated Journal | JEMR |
| Volume | 7 | Issue | 3 | Pages | 1-10 |
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| Abstract | We analyze the feasibility of a cheap eye-tracker where the hardware consists of a single webcam and a Raspberry Pi device. Our aim is to discover the limits of such a system and to see whether it provides an acceptable performance. We base our work on the open source Opengazer (Zielinski, 2013) and we propose several improvements to create a robust, real-time system which can work on a computer with 30Hz sampling rate. After assessing the accuracy of our eye-tracker in elaborated experiments involving 12 subjects under 4 different system setups, we install it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.42° horizontal accuracy with 3Hz refresh rate for a building cost of 70 Euros. | ||||
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| Notes | ;SIAI | Approved | no | ||
| Call Number | Admin @ si @ FVS2014 | Serial | 2435 | ||
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| Author | Oscar Lopes; Miguel Reyes; Sergio Escalera; Jordi Gonzalez | ||||
| Title | Spherical Blurred Shape Model for 3-D Object and Pose Recognition: Quantitative Analysis and HCI Applications in Smart Environments | Type | Journal Article | ||
| Year | 2014 | Publication | IEEE Transactions on Systems, Man and Cybernetics (Part B) | Abbreviated Journal | TSMCB |
| Volume | 44 | Issue | 12 | Pages | 2379-2390 |
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| Abstract | The use of depth maps is of increasing interest after the advent of cheap multisensor devices based on structured light, such as Kinect. In this context, there is a strong need of powerful 3-D shape descriptors able to generate rich object representations. Although several 3-D descriptors have been already proposed in the literature, the research of discriminative and computationally efficient descriptors is still an open issue. In this paper, we propose a novel point cloud descriptor called spherical blurred shape model (SBSM) that successfully encodes the structure density and local variabilities of an object based on shape voxel distances and a neighborhood propagation strategy. The proposed SBSM is proven to be rotation and scale invariant, robust to noise and occlusions, highly discriminative for multiple categories of complex objects like the human hand, and computationally efficient since the SBSM complexity is linear to the number of object voxels. Experimental evaluation in public depth multiclass object data, 3-D facial expressions data, and a novel hand poses data sets show significant performance improvements in relation to state-of-the-art approaches. Moreover, the effectiveness of the proposal is also proved for object spotting in 3-D scenes and for real-time automatic hand pose recognition in human computer interaction scenarios. | ||||
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| ISSN | 2168-2267 | ISBN | Medium | ||
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| Notes | HuPBA; ISE; 600.078;MILAB | Approved | no | ||
| Call Number | Admin @ si @ LRE2014 | Serial | 2442 | ||
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| Author | Xavier Perez Sala; Sergio Escalera; Cecilio Angulo; Jordi Gonzalez | ||||
| Title | A survey on model based approaches for 2D and 3D visual human pose recovery | Type | Journal Article | ||
| Year | 2014 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 14 | Issue | 3 | Pages | 4189-4210 |
| Keywords | human pose recovery; human body modelling; behavior analysis; computer vision | ||||
| Abstract | Human Pose Recovery has been studied in the field of Computer Vision for the last 40 years. Several approaches have been reported, and significant improvements have been obtained in both data representation and model design. However, the problem of Human Pose Recovery in uncontrolled environments is far from being solved. In this paper, we define a general taxonomy to group model based approaches for Human Pose Recovery, which is composed of five main modules: appearance, viewpoint, spatial relations, temporal consistence, and behavior. Subsequently, a methodological comparison is performed following the proposed taxonomy, evaluating current SoA approaches in the aforementioned five group categories. As a result of this comparison, we discuss the main advantages and drawbacks of the reviewed literature. | ||||
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| Notes | HuPBA; ISE; 600.046; 600.063; 600.078;MILAB | Approved | no | ||
| Call Number | Admin @ si @ PEA2014 | Serial | 2443 | ||
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| Author | Frederic Sampedro; Anna Domenech; Sergio Escalera | ||||
| Title | Obtaining quantitative global tumoral state indicators based on whole-body PET/CT scans: A breast cancer case study | Type | Journal Article | ||
| Year | 2014 | Publication | Nuclear Medicine Communications | Abbreviated Journal | NMC |
| Volume | 35 | Issue | 4 | Pages | 362-371 |
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| Abstract | Objectives: In this work we address the need for the computation of quantitative global tumoral state indicators from oncological whole-body PET/computed tomography scans. The combination of such indicators with other oncological information such as tumor markers or biopsy results would prove useful in oncological decision-making scenarios.
Materials and methods: From an ordering of 100 breast cancer patients on the basis of oncological state through visual analysis by a consensus of nuclear medicine specialists, a set of numerical indicators computed from image analysis of the PET/computed tomography scan is presented, which attempts to summarize a patient’s oncological state in a quantitative manner taking into consideration the total tumor volume, aggressiveness, and spread. Results: Results obtained by comparative analysis of the proposed indicators with respect to the experts’ evaluation show up to 87% Pearson’s correlation coefficient when providing expert-guided PET metabolic tumor volume segmentation and 64% correlation when using completely automatic image analysis techniques. Conclusion: Global quantitative tumor information obtained by whole-body PET/CT image analysis can prove useful in clinical nuclear medicine settings and oncological decision-making scenarios. The completely automatic computation of such indicators would improve its impact as time efficiency and specialist independence would be achieved. |
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | SDE2014a | Serial | 2444 | ||
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| Author | Shida Beigpour; Christian Riess; Joost Van de Weijer; Elli Angelopoulou | ||||
| Title | Multi-Illuminant Estimation with Conditional Random Fields | Type | Journal Article | ||
| Year | 2014 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
| Volume | 23 | Issue | 1 | Pages | 83-95 |
| Keywords | color constancy; CRF; multi-illuminant | ||||
| Abstract | Most existing color constancy algorithms assume uniform illumination. However, in real-world scenes, this is not often the case. Thus, we propose a novel framework for estimating the colors of multiple illuminants and their spatial distribution in the scene. We formulate this problem as an energy minimization task within a conditional random field over a set of local illuminant estimates. In order to quantitatively evaluate the proposed method, we created a novel data set of two-dominant-illuminant images comprised of laboratory, indoor, and outdoor scenes. Unlike prior work, our database includes accurate pixel-wise ground truth illuminant information. The performance of our method is evaluated on multiple data sets. Experimental results show that our framework clearly outperforms single illuminant estimators as well as a recently proposed multi-illuminant estimation approach. | ||||
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| ISSN | 1057-7149 | ISBN | Medium | ||
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| Notes | CIC; LAMP; 600.074; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ BRW2014 | Serial | 2451 | ||
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| Author | David Masip; Michael S. North ; Alexander Todorov; Daniel N. Osherson | ||||
| Title | Automated Prediction of Preferences Using Facial Expressions | Type | Journal Article | ||
| Year | 2014 | Publication | PloS one | Abbreviated Journal | Plos |
| Volume | 9 | Issue | 2 | Pages | e87434 |
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| Abstract | We introduce a computer vision problem from social cognition, namely, the automated detection of attitudes from a person's spontaneous facial expressions. To illustrate the challenges, we introduce two simple algorithms designed to predict observers’ preferences between images (e.g., of celebrities) based on covert videos of the observers’ faces. The two algorithms are almost as accurate as human judges performing the same task but nonetheless far from perfect. Our approach is to locate facial landmarks, then predict preference on the basis of their temporal dynamics. The database contains 768 videos involving four different kinds of preferences. We make it publically available. | ||||
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| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ MNT2014 | Serial | 2453 | ||
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| Author | David Fernandez; Josep Llados; Alicia Fornes | ||||
| Title | A graph-based approach for segmenting touching lines in historical handwritten documents | Type | Journal Article | ||
| Year | 2014 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume | 17 | Issue | 3 | Pages | 293-312 |
| Keywords | Text line segmentation; Handwritten documents; Document image processing; Historical document analysis | ||||
| Abstract | Text line segmentation in handwritten documents is an important task in the recognition of historical documents. Handwritten document images contain text lines with multiple orientations, touching and overlapping characters between consecutive text lines and different document structures, making line segmentation a difficult task. In this paper, we present a new approach for handwritten text line segmentation solving the problems of touching components, curvilinear text lines and horizontally overlapping components. The proposed algorithm formulates line segmentation as finding the central path in the area between two consecutive lines. This is solved as a graph traversal problem. A graph is constructed using the skeleton of the image. Then, a path-finding algorithm is used to find the optimum path between text lines. The proposed algorithm has been evaluated on a comprehensive dataset consisting of five databases: ICDAR2009, ICDAR2013, UMD, the George Washington and the Barcelona Marriages Database. The proposed method outperforms the state-of-the-art considering the different types and difficulties of the benchmarking data. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| ISSN | 1433-2833 | ISBN | Medium | ||
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| Notes | DAG; 600.056; 600.061; 602.006; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ FLF2014 | Serial | 2459 | ||
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| Author | Monica Piñol | ||||
| Title | Reinforcement Learning of Visual Descriptors for Object Recognition | Type | Book Whole | ||
| Year | 2014 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | The human visual system is able to recognize the object in an image even if the object is partially occluded, from various points of view, in different colors, or with independence of the distance to the object. To do this, the eye obtains an image and extracts features that are sent to the brain, and then, in the brain the object is recognized. In computer vision, the object recognition branch tries to learns from the human visual system behaviour to achieve its goal. Hence, an algorithm is used to identify representative features of the scene (detection), then another algorithm is used to describe these points (descriptor) and finally the extracted information is used for classifying the object in the scene. The selection of this set of algorithms is a very complicated task and thus, a very active research field. In this thesis we are focused on the selection/learning of the best descriptor for a given image. In the state of the art there are several descriptors but we do not know how to choose the best descriptor because depends on scenes that we will use (dataset) and the algorithm chosen to do the classification. We propose a framework based on reinforcement learning and bag of features to choose the best descriptor according to the given image. The system can analyse the behaviour of different learning algorithms and descriptor sets. Furthermore the proposed framework for improving the classification/recognition ratio can be used with minor changes in other computer vision fields, such as video retrieval. | ||||
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Ricardo Toledo;Angel Sappa | |
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| ISSN | ISBN | 978-84-940902-5-7 | Medium | ||
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| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ Piñ2014 | Serial | 2464 | ||
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| Author | Anjan Dutta | ||||
| Title | Inexact Subgraph Matching Applied to Symbol Spotting in Graphical Documents | Type | Book Whole | ||
| Year | 2014 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | There is a resurgence in the use of structural approaches in the usual object recognition and retrieval problem. Graph theory, in particular, graph matching plays a relevant role in that. Specifically, the detection of an object (or a part of that) in an image in terms of structural features can be formulated as a subgraph matching. Subgraph matching is a challenging task. Specially due to the presence of outliers most of the graph matching algorithms do not perform well in subgraph matching scenario. Also exact subgraph isomorphism has proven to be an NP-complete problem. So naturally, in graph matching community, there are lot of efforts addressing the problem of subgraph matching within suboptimal bound. Most of them work with approximate algorithms that try to get an inexact solution in estimated way. In addition, usual recognition must cope with distortion. Inexact graph matching consists in finding the best isomorphism under a similarity measure. Theoretically this thesis proposes algorithms for solving subgraph matching in an approximate and inexact way.
We consider the symbol spotting problem on graphical documents or line drawings from application point of view. This is a well known problem in the graphics recognition community. It can be further applied for indexing and classification of documents based on their contents. The structural nature of this kind of documents easily motivates one for giving a graph based representation. So the symbol spotting problem on graphical documents can be considered as a subgraph matching problem. The main challenges in this application domain is the noise and distortions that might come during the usage, digitalization and raster to vector conversion of those documents. Apart from that computer vision nowadays is not any more confined within a limited number of images. So dealing a huge number of images with graph based method is a further challenge. In this thesis, on one hand, we have worked on efficient and robust graph representation to cope with the noise and distortions coming from documents. On the other hand, we have worked on different graph based methods and framework to solve the subgraph matching problem in a better approximated way, which can also deal with considerable number of images. Firstly, we propose a symbol spotting method by hashing serialized subgraphs. Graph serialization allows to create factorized substructures such as graph paths, which can be organized in hash tables depending on the structural similarities of the serialized subgraphs. The involvement of hashing techniques helps to reduce the search space substantially and speeds up the spotting procedure. Secondly, we introduce contextual similarities based on the walk based propagation on tensor product graph. These contextual similarities involve higher order information and more reliable than pairwise similarities. We use these higher order similarities to formulate subgraph matching as a node and edge selection problem in the tensor product graph. Thirdly, we propose near convex grouping to form near convex region adjacency graph which eliminates the limitations of traditional region adjacency graph representation for graphic recognition. Fourthly, we propose a hierarchical graph representation by simplifying/correcting the structural errors to create a hierarchical graph of the base graph. Later these hierarchical graph structures are matched with some graph matching methods. Apart from that, in this thesis we have provided an overall experimental comparison of all the methods and some of the state-of-the-art methods. Furthermore, some dataset models have also been proposed. |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Josep Llados;Umapada Pal | |
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| ISSN | ISBN | 978-84-940902-4-0 | Medium | ||
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| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ Dut2014 | Serial | 2465 | ||
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| Author | Carlo Gatta; Francesco Ciompi | ||||
| Title | Stacked Sequential Scale-Space Taylor Context | Type | Journal Article | ||
| Year | 2014 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 36 | Issue | 8 | Pages | 1694-1700 |
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| Abstract | We analyze sequential image labeling methods that sample the posterior label field in order to gather contextual information. We propose an effective method that extracts local Taylor coefficients from the posterior at different scales. Results show that our proposal outperforms state-of-the-art methods on MSRC-21, CAMVID, eTRIMS8 and KAIST2 data sets. | ||||
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| ISSN | 0162-8828 | ISBN | Medium | ||
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| Notes | LAMP; MILAB; 601.160; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ GaC2014 | Serial | 2466 | ||
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| Author | Pedro Martins; Paulo Carvalho; Carlo Gatta | ||||
| Title | Context-aware features and robust image representations | Type | Journal Article | ||
| Year | 2014 | Publication | Journal of Visual Communication and Image Representation | Abbreviated Journal | JVCIR |
| Volume | 25 | Issue | 2 | Pages | 339-348 |
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| Abstract | Local image features are often used to efficiently represent image content. The limited number of types of features that a local feature extractor responds to might be insufficient to provide a robust image representation. To overcome this limitation, we propose a context-aware feature extraction formulated under an information theoretic framework. The algorithm does not respond to a specific type of features; the idea is to retrieve complementary features which are relevant within the image context. We empirically validate the method by investigating the repeatability, the completeness, and the complementarity of context-aware features on standard benchmarks. In a comparison with strictly local features, we show that our context-aware features produce more robust image representations. Furthermore, we study the complementarity between strictly local features and context-aware ones to produce an even more robust representation. | ||||
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| Notes | LAMP; 600.079;MILAB | Approved | no | ||
| Call Number | Admin @ si @ MCG2014 | Serial | 2467 | ||
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| Author | Simeon Petkov; Xavier Carrillo; Petia Radeva; Carlo Gatta | ||||
| Title | Diaphragm border detection in coronary X-ray angiographies: New method and applications | Type | Journal Article | ||
| Year | 2014 | Publication | Computerized Medical Imaging and Graphics | Abbreviated Journal | CMIG |
| Volume | 38 | Issue | 4 | Pages | 296-305 |
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| Abstract | X-ray angiography is widely used in cardiac disease diagnosis during or prior to intravascular interventions. The diaphragm motion and the heart beating induce gray-level changes, which are one of the main obstacles in quantitative analysis of myocardial perfusion. In this paper we focus on detecting the diaphragm border in both single images or whole X-ray angiography sequences. We show that the proposed method outperforms state of the art approaches. We extend a previous publicly available data set, adding new ground truth data. We also compose another set of more challenging images, thus having two separate data sets of increasing difficulty. Finally, we show three applications of our method: (1) a strategy to reduce false positives in vessel enhanced images; (2) a digital diaphragm removal algorithm; (3) an improvement in Myocardial Blush Grade semi-automatic estimation. | ||||
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| Notes | MILAB; LAMP; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ PCR2014 | Serial | 2468 | ||
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| Author | Pierluigi Casale; Oriol Pujol; Petia Radeva | ||||
| Title | Approximate polytope ensemble for one-class classification | Type | Journal Article | ||
| Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 47 | Issue | 2 | Pages | 854-864 |
| Keywords | One-class classification; Convex hull; High-dimensionality; Random projections; Ensemble learning | ||||
| Abstract | In this work, a new one-class classification ensemble strategy called approximate polytope ensemble is presented. The main contribution of the paper is threefold. First, the geometrical concept of convex hull is used to define the boundary of the target class defining the problem. Expansions and contractions of this geometrical structure are introduced in order to avoid over-fitting. Second, the decision whether a point belongs to the convex hull model in high dimensional spaces is approximated by means of random projections and an ensemble decision process. Finally, a tiling strategy is proposed in order to model non-convex structures. Experimental results show that the proposed strategy is significantly better than state of the art one-class classification methods on over 200 datasets. | ||||
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| Notes | MILAB; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ CPR2014a | Serial | 2469 | ||
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| Author | Francesco Ciompi; Oriol Pujol; Petia Radeva | ||||
| Title | ECOC-DRF: Discriminative random fields based on error correcting output codes | Type | Journal Article | ||
| Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 47 | Issue | 6 | Pages | 2193-2204 |
| Keywords | Discriminative random fields; Error-correcting output codes; Multi-class classification; Graphical models | ||||
| Abstract | We present ECOC-DRF, a framework where potential functions for Discriminative Random Fields are formulated as an ensemble of classifiers. We introduce the label trick, a technique to express transitions in the pairwise potential as meta-classes. This allows to independently learn any possible transition between labels without assuming any pre-defined model. The Error Correcting Output Codes matrix is used as ensemble framework for the combination of margin classifiers. We apply ECOC-DRF to a large set of classification problems, covering synthetic, natural and medical images for binary and multi-class cases, outperforming state-of-the art in almost all the experiments. | ||||
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| Notes | LAMP; HuPBA; MILAB; 605.203; 600.046; 601.043; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ CPR2014b | Serial | 2470 | ||
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| Author | Adriana Romero; Petia Radeva; Carlo Gatta | ||||
| Title | No more meta-parameter tuning in unsupervised sparse feature learning | Type | Miscellaneous | ||
| Year | 2014 | Publication | Arxiv | Abbreviated Journal | |
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| Abstract | CoRR abs/1402.5766
We propose a meta-parameter free, off-the-shelf, simple and fast unsupervised feature learning algorithm, which exploits a new way of optimizing for sparsity. Experiments on STL-10 show that the method presents state-of-the-art performance and provides discriminative features that generalize well. |
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| Notes | MILAB; LAMP; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ RRG2014 | Serial | 2471 | ||
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