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| Author | Jaume Amores | ||||
| Title | MILDE: multiple instance learning by discriminative embedding | Type | Journal Article | ||
| Year | 2015 | Publication | Knowledge and Information Systems | Abbreviated Journal | KAIS |
| Volume | 42 | Issue | 2 | Pages | 381-407 |
| Keywords | Multi-instance learning; Codebook; Bag of words | ||||
| Abstract | While the objective of the standard supervised learning problem is to classify feature vectors, in the multiple instance learning problem, the objective is to classify bags, where each bag contains multiple feature vectors. This represents a generalization of the standard problem, and this generalization becomes necessary in many real applications such as drug activity prediction, content-based image retrieval, and others. While the existing paradigms are based on learning the discriminant information either at the instance level or at the bag level, we propose to incorporate both levels of information. This is done by defining a discriminative embedding of the original space based on the responses of cluster-adapted instance classifiers. Results clearly show the advantage of the proposed method over the state of the art, where we tested the performance through a variety of well-known databases that come from real problems, and we also included an analysis of the performance using synthetically generated data. | ||||
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| Publisher | Springer London | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
ISSN  |
0219-1377 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS; 601.042; 600.057; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ Amo2015 | Serial | 2383 | ||
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| Author | Ester Fornells; Manuel De Armas; Maria Teresa Anguera; Sergio Escalera; Marcos Antonio Catalán; Josep Moya | ||||
| Title | Desarrollo del proyecto del Consell Comarcal del Baix Llobregat “Buen Trato a las personas mayores y aquellas en situación de fragilidad con sufrimiento emocional: Hacia un envejecimiento saludable” | Type | Journal | ||
| Year | 2018 | Publication | Informaciones Psiquiatricas | Abbreviated Journal | |
| Volume | 232 | Issue | Pages | 47-59 | |
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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 |
0210-7279 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | HUPBA; no menciona | Approved | no | ||
| Call Number | Admin @ si @ FAA2018 | Serial | 3214 | ||
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| Author | Adriana Romero; Carlo Gatta; Gustavo Camps-Valls | ||||
| Title | Unsupervised Deep Feature Extraction for Remote Sensing Image Classification | Type | Journal Article | ||
| Year | 2016 | Publication | IEEE Transaction on Geoscience and Remote Sensing | Abbreviated Journal | TGRS |
| Volume | 54 | Issue | 3 | Pages | 1349 - 1362 |
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| Abstract | This paper introduces the use of single-layer and deep convolutional networks for remote sensing data analysis. Direct application to multi- and hyperspectral imagery of supervised (shallow or deep) convolutional networks is very challenging given the high input data dimensionality and the relatively small amount of available labeled data. Therefore, we propose the use of greedy layerwise unsupervised pretraining coupled with a highly efficient algorithm for unsupervised learning of sparse features. The algorithm is rooted on sparse representations and enforces both population and lifetime sparsity of the extracted features, simultaneously. We successfully illustrate the expressive power of the extracted representations in several scenarios: classification of aerial scenes, as well as land-use classification in very high resolution or land-cover classification from multi- and hyperspectral images. The proposed algorithm clearly outperforms standard principal component analysis (PCA) and its kernel counterpart (kPCA), as well as current state-of-the-art algorithms of aerial classification, while being extremely computationally efficient at learning representations of data. Results show that single-layer convolutional networks can extract powerful discriminative features only when the receptive field accounts for neighboring pixels and are preferred when the classification requires high resolution and detailed results. However, deep architectures significantly outperform single-layer variants, capturing increasing levels of abstraction and complexity throughout the feature hierarchy. | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0196-2892 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | LAMP; 600.079;MILAB | Approved | no | ||
| Call Number | Admin @ si @ RGC2016 | Serial | 2723 | ||
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| Author | Miquel Ferrer; Ernest Valveny; F. Serratosa | ||||
| Title | Median graph: A new exact algorithm using a distance based on the maximum common subgraph | Type | Journal Article | ||
| Year | 2009 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 30 | Issue | 5 | Pages | 579–588 |
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| Abstract | Median graphs have been presented as a useful tool for capturing the essential information of a set of graphs. Nevertheless, computation of optimal solutions is a very hard problem. In this work we present a new and more efficient optimal algorithm for the median graph computation. With the use of a particular cost function that permits the definition of the graph edit distance in terms of the maximum common subgraph, and a prediction function in the backtracking algorithm, we reduce the size of the search space, avoiding the evaluation of a great amount of states and still obtaining the exact median. We present a set of experiments comparing our new algorithm against the previous existing exact algorithm using synthetic data. In addition, we present the first application of the exact median graph computation to real data and we compare the results against an approximate algorithm based on genetic search. These experimental results show that our algorithm outperforms the previous existing exact algorithm and in addition show the potential applicability of the exact solutions to real problems. | ||||
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| Publisher | Elsevier Science Inc. | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ FVS2009a | Serial | 1114 | ||
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| Author | Fadi Dornaika; Angel Sappa | ||||
| Title | Instantaneous 3D motion from image derivatives using the Least Trimmed Square Regression | Type | Journal Article | ||
| Year | 2009 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 30 | Issue | 5 | Pages | 535–543 |
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| Abstract | This paper presents a new technique to the instantaneous 3D motion estimation. The main contributions are as follows. First, we show that the 3D camera or scene velocity can be retrieved from image derivatives only assuming that the scene contains a dominant plane. Second, we propose a new robust algorithm that simultaneously provides the Least Trimmed Square solution and the percentage of inliers-the non-contaminated data. Experiments on both synthetic and real image sequences demonstrated the effectiveness of the developed method. Those experiments show that the new robust approach can outperform classical robust schemes. | ||||
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| Publisher | Elsevier Science Inc. | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ DoS2009a | Serial | 1115 | ||
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| Author | Debora Gil; Petia Radeva | ||||
| Title | Inhibition of false landmarks | Type | Journal Article | ||
| Year | 2006 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 27 | Issue | 9 | Pages | 1022-1030 |
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| Abstract | Corners and junctions are landmarks characterized by the lack of differentiability in the unit tangent to the image level curve. Detectors based on differential operators are not, by their own definition, the best posed as they require a higher degree of differentiability to yield a reliable response. We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our inhibition orientation energy (IOE) landmark locator. | ||||
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| Publisher | Elsevier Science Inc. | Place of Publication | New York, NY, USA | Editor | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | IAM;MILAB | Approved | no | ||
| Call Number | IAM @ iam @ GiR2006 | Serial | 1529 | ||
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| Author | Ernest Valveny; Enric Marti | ||||
| Title | A model for image generation and symbol recognition through the deformation of lineal shapes | Type | Journal Article | ||
| Year | 2003 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 24 | Issue | 15 | Pages | 2857-2867 |
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| Abstract | We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents. | ||||
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| Publisher | Elsevier Science Inc. | Place of Publication | New York, NY, USA | Editor | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; IAM | Approved | no | ||
| Call Number | IAM @ iam @ VAM2003 | Serial | 1653 | ||
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| Author | Sergio Escalera; David Masip; Eloi Puertas; Petia Radeva; Oriol Pujol | ||||
| Title | Online Error-Correcting Output Codes | Type | Journal Article | ||
| Year | 2011 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 32 | Issue | 3 | Pages | 458-467 |
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| Abstract | IF JCR CCIA 1.303 2009 54/103
This article proposes a general extension of the error correcting output codes framework to the online learning scenario. As a result, the final classifier handles the addition of new classes independently of the base classifier used. In particular, this extension supports the use of both online example incremental and batch classifiers as base learners. The extension of the traditional problem independent codings one-versus-all and one-versus-one is introduced. Furthermore, two new codings are proposed, unbalanced online ECOC and a problem dependent online ECOC. This last online coding technique takes advantage of the problem data for minimizing the number of dichotomizers used in the ECOC framework while preserving a high accuracy. These techniques are validated on an online setting of 11 data sets from UCI database and applied to two real machine vision applications: traffic sign recognition and face recognition. As a result, the online ECOC techniques proposed provide a feasible and robust way for handling new classes using any base classifier. |
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| Publisher | Elsevier | Place of Publication | North Holland | Editor | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB;OR;HuPBA;MV | Approved | no | ||
| Call Number | Admin @ si @ EMP2011 | Serial | 1714 | ||
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| Author | Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Petia Radeva; Jordi Vitria; Oriol Pujol | ||||
| Title | Minimal Design of Error-Correcting Output Codes | Type | Journal Article | ||
| Year | 2011 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 33 | Issue | 6 | Pages | 693-702 |
| Keywords | Multi-class classification; Error-correcting output codes; Ensemble of classifiers | ||||
| Abstract | IF JCR CCIA 1.303 2009 54/103
The classification of large number of object categories is a challenging trend in the pattern recognition field. In literature, this is often addressed using an ensemble of classifiers. In this scope, the Error-correcting output codes framework has demonstrated to be a powerful tool for combining classifiers. However, most state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a minimal design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best minimal ECOC code configuration. The results over several public UCI datasets and different multi-class computer vision problems show that the proposed methodology obtains comparable (even better) results than state-of-the-art ECOC methodologies with far less number of dichotomizers. |
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB; OR;HuPBA;MV | Approved | no | ||
| Call Number | Admin @ si @ BEB2011a | Serial | 1800 | ||
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| Author | David Sanchez-Mendoza; David Masip; Agata Lapedriza | ||||
| Title | Emotion recognition from mid-level features | Type | Journal Article | ||
| Year | 2015 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 67 | Issue | Part 1 | Pages | 66–74 |
| Keywords | Facial expression; Emotion recognition; Action units; Computer vision | ||||
| Abstract | In this paper we present a study on the use of Action Units as mid-level features for automatically recognizing basic and subtle emotions. We propose a representation model based on mid-level facial muscular movement features. We encode these movements dynamically using the Facial Action Coding System, and propose to use these intermediate features based on Action Units (AUs) to classify emotions. AUs activations are detected fusing a set of spatiotemporal geometric and appearance features. The algorithm is validated in two applications: (i) the recognition of 7 basic emotions using the publicly available Cohn-Kanade database, and (ii) the inference of subtle emotional cues in the Newscast database. In this second scenario, we consider emotions that are perceived cumulatively in longer periods of time. In particular, we Automatically classify whether video shoots from public News TV channels refer to Good or Bad news. To deal with the different video lengths we propose a Histogram of Action Units and compute it using a sliding window strategy on the frame sequences. Our approach achieves accuracies close to human perception. | ||||
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| Publisher | Elsevier B.V. | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ SML2015 | Serial | 2746 | ||
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| Author | Pedro Martins; Paulo Carvalho; Carlo Gatta | ||||
| Title | On the completeness of feature-driven maximally stable extremal regions | Type | Journal Article | ||
| Year | 2016 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 74 | Issue | Pages | 9-16 | |
| Keywords | Local features; Completeness; Maximally Stable Extremal Regions | ||||
| Abstract | By definition, local image features provide a compact representation of the image in which most of the image information is preserved. This capability offered by local features has been overlooked, despite being relevant in many application scenarios. In this paper, we analyze and discuss the performance of feature-driven Maximally Stable Extremal Regions (MSER) in terms of the coverage of informative image parts (completeness). This type of features results from an MSER extraction on saliency maps in which features related to objects boundaries or even symmetry axes are highlighted. These maps are intended to be suitable domains for MSER detection, allowing this detector to provide a better coverage of informative image parts. Our experimental results, which were based on a large-scale evaluation, show that feature-driven MSER have relatively high completeness values and provide more complete sets than a traditional MSER detection even when sets of similar cardinality are considered. | ||||
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| Publisher | Elsevier B.V. | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0167-8655 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | LAMP;MILAB; | Approved | no | ||
| Call Number | Admin @ si @ MCG2016 | Serial | 2748 | ||
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| Author | Enric Marti; Jordi Regincos;Jaime Lopez-Krahe; Juan J.Villanueva | ||||
| Title | Hand line drawing interpretation as three-dimensional objects | Type | Journal Article | ||
| Year | 1993 | Publication | Signal Processing – Intelligent systems for signal and image understanding | Abbreviated Journal | |
| Volume | 32 | Issue | 1-2 | Pages | 91-110 |
| Keywords | Line drawing interpretation; line labelling; scene analysis; man-machine interaction; CAD input; line extraction | ||||
| Abstract | In this paper we present a technique to interpret hand line drawings as objects in a three-dimensional space. The object domain considered is based on planar surfaces with straight edges, concretely, on ansextension of Origami world to hidden lines. The line drawing represents the object under orthographic projection and it is sensed using a scanner. Our method is structured in two modules: feature extraction and feature interpretation. In the first one, image processing techniques are applied under certain tolerance margins to detect lines and junctions on the hand line drawing. Feature interpretation module is founded on line labelling techniques using a labelled junction dictionary. A labelling algorithm is here proposed. It uses relaxation techniques to reduce the number of incompatible labels with the junction dictionary so that the convergence of solutions can be accelerated. We formulate some labelling hypotheses tending to eliminate elements in two sets of labelled interpretations. That is, those which are compatible with the dictionary but do not correspond to three-dimensional objects and those which represent objects not very probable to be specified by means of a line drawing. New entities arise on the line drawing as a result of the extension of Origami world. These are defined to enunciate the assumptions of our method as well as to clarify the algorithms proposed. This technique is framed in a project aimed to implement a system to create 3D objects to improve man-machine interaction in CAD systems. | ||||
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| Publisher | Elsevier North-Holland, Inc. | Place of Publication | Amsterdam, The Netherlands, The Netherlands | Editor | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN |
0165-1684 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | IAM;ISE; | Approved | no | ||
| Call Number | IAM @ iam @ MRL1993 | Serial | 1611 | ||
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| Author | Albert Gordo; Florent Perronnin; Yunchao Gong; Svetlana Lazebnik | ||||
| Title | Asymmetric Distances for Binary Embeddings | Type | Journal Article | ||
| Year | 2014 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 36 | Issue | 1 | Pages | 33-47 |
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| Abstract | In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH), PCA Embedding (PCAE), PCA Embedding with random rotations (PCAE-RR), and PCA Embedding with iterative quantization (PCAE-ITQ). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN |
0162-8828 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.045; 605.203; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ GPG2014 | Serial | 2272 | ||
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| Author | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
| Title | Domain Adaptation of Deformable Part-Based Models | Type | Journal Article | ||
| Year | 2014 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 36 | Issue | 12 | Pages | 2367-2380 |
| Keywords | Domain Adaptation; Pedestrian Detection | ||||
| Abstract | The accuracy of object classifiers can significantly drop when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, adapting the classifiers to the scenario in which they must operate is of paramount importance. We present novel domain adaptation (DA) methods for object detection. As proof of concept, we focus on adapting the state-of-the-art deformable part-based model (DPM) for pedestrian detection. We introduce an adaptive structural SVM (A-SSVM) that adapts a pre-learned classifier between different domains. By taking into account the inherent structure in feature space (e.g., the parts in a DPM), we propose a structure-aware A-SSVM (SA-SSVM). Neither A-SSVM nor SA-SSVM needs to revisit the source-domain training data to perform the adaptation. Rather, a low number of target-domain training examples (e.g., pedestrians) are used. To address the scenario where there are no target-domain annotated samples, we propose a self-adaptive DPM based on a self-paced learning (SPL) strategy and a Gaussian Process Regression (GPR). Two types of adaptation tasks are assessed: from both synthetic pedestrians and general persons (PASCAL VOC) to pedestrians imaged from an on-board camera. Results show that our proposals avoid accuracy drops as high as 15 points when comparing adapted and non-adapted detectors. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN |
0162-8828 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS; 600.057; 600.054; 601.217; 600.076 | Approved | no | ||
| Call Number | ADAS @ adas @ XRV2014b | Serial | 2436 | ||
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| Author | Oriol Ramos Terrades; Ernest Valveny; Salvatore Tabbone | ||||
| Title | Optimal Classifier Fusion in a Non-Bayesian Probabilistic Framework | Type | Journal Article | ||
| Year | 2009 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 31 | Issue | 9 | Pages | 1630–1644 |
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| Abstract | The combination of the output of classifiers has been one of the strategies used to improve classification rates in general purpose classification systems. Some of the most common approaches can be explained using the Bayes' formula. In this paper, we tackle the problem of the combination of classifiers using a non-Bayesian probabilistic framework. This approach permits us to derive two linear combination rules that minimize misclassification rates under some constraints on the distribution of classifiers. In order to show the validity of this approach we have compared it with other popular combination rules from a theoretical viewpoint using a synthetic data set, and experimentally using two standard databases: the MNIST handwritten digit database and the GREC symbol database. Results on the synthetic data set show the validity of the theoretical approach. Indeed, results on real data show that the proposed methods outperform other common combination schemes. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN |
0162-8828 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RVT2009 | Serial | 1220 | ||
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