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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 | Lichao Zhang; Abel Gonzalez-Garcia; Joost Van de Weijer; Martin Danelljan; Fahad Shahbaz Khan | ||||
Title | Synthetic Data Generation for End-to-End Thermal Infrared Tracking | Type | Journal Article | ||
Year | 2019 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 28 | Issue | 4 | Pages | 1837 - 1850 |
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Abstract | The usage of both off-the-shelf and end-to-end trained deep networks have significantly improved the performance of visual tracking on RGB videos. However, the lack of large labeled datasets hampers the usage of convolutional neural networks for tracking in thermal infrared (TIR) images. Therefore, most state-of-the-art methods on tracking for TIR data are still based on handcrafted features. To address this problem, we propose to use image-to-image translation models. These models allow us to translate the abundantly available labeled RGB data to synthetic TIR data. We explore both the usage of paired and unpaired image translation models for this purpose. These methods provide us with a large labeled dataset of synthetic TIR sequences, on which we can train end-to-end optimal features for tracking. To the best of our knowledge, we are the first to train end-to-end features for TIR tracking. We perform extensive experiments on the VOT-TIR2017 dataset. We show that a network trained on a large dataset of synthetic TIR data obtains better performance than one trained on the available real TIR data. Combining both data sources leads to further improvement. In addition, when we combine the network with motion features, we outperform the state of the art with a relative gain of over 10%, clearly showing the efficiency of using synthetic data to train end-to-end TIR trackers. | ||||
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Notes | LAMP; 600.141; 600.120 | Approved | no | ||
Call Number | Admin @ si @ YGW2019 | Serial | 3228 | ||
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Author | Albert Ali Salah; E. Pauwels; R. Tavenard; Theo Gevers | ||||
Title | T-Patterns Revisited: Mining for Temporal Patterns in Sensor Data | Type | Journal Article | ||
Year | 2010 | Publication | Sensors | Abbreviated Journal | SENS |
Volume | 10 | Issue | 8 | Pages | 7496-7513 |
Keywords | sensor networks; temporal pattern extraction; T-patterns; Lempel-Ziv; Gaussian mixture model; MERL motion data | ||||
Abstract | The trend to use large amounts of simple sensors as opposed to a few complex sensors to monitor places and systems creates a need for temporal pattern mining algorithms to work on such data. The methods that try to discover re-usable and interpretable patterns in temporal event data have several shortcomings. We contrast several recent approaches to the problem, and extend the T-Pattern algorithm, which was previously applied for detection of sequential patterns in behavioural sciences. The temporal complexity of the T-pattern approach is prohibitive in the scenarios we consider. We remedy this with a statistical model to obtain a fast and robust algorithm to find patterns in temporal data. We test our algorithm on a recent database collected with passive infrared sensors with millions of events. | ||||
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Notes | ALTRES;ISE | Approved | no | ||
Call Number | Admin @ si @ SPT2010 | Serial | 1845 | ||
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Author | Sergio Escalera; Jordi Gonzalez; Xavier Baro; Jamie Shotton | ||||
Title | Guest Editor Introduction to the Special Issue on Multimodal Human Pose Recovery and Behavior Analysis | Type | Journal Article | ||
Year | 2016 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 28 | Issue | Pages | 1489 - 1491 | |
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Abstract | The sixteen papers in this special section focus on human pose recovery and behavior analysis (HuPBA). This is one of the most challenging topics in computer vision, pattern analysis, and machine learning. It is of critical importance for application areas that include gaming, computer interaction, human robot interaction, security, commerce, assistive technologies and rehabilitation, sports, sign language recognition, and driver assistance technology, to mention just a few. In essence, HuPBA requires dealing with the articulated nature of the human body, changes in appearance due to clothing, and the inherent problems of clutter scenes, such as background artifacts, occlusions, and illumination changes. These papers represent the most recent research in this field, including new methods considering still images, image sequences, depth data, stereo vision, 3D vision, audio, and IMUs, among others. | ||||
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Notes | HuPBA; ISE;MV; | Approved | no | ||
Call Number | Admin @ si @ | Serial | 2851 | ||
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Author | C. Alejandro Parraga; Arash Akbarinia | ||||
Title | NICE: A Computational Solution to Close the Gap from Colour Perception to Colour Categorization | Type | Journal Article | ||
Year | 2016 | Publication | PLoS One | Abbreviated Journal | Plos |
Volume | 11 | Issue | 3 | Pages | e0149538 |
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Abstract | The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms. | ||||
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Notes | NEUROBIT; 600.068 | Approved | no | ||
Call Number | Admin @ si @ PaA2016a | Serial | 2747 | ||
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Author | Eduard Vazquez; Ramon Baldrich; Joost Van de Weijer; Maria Vanrell | ||||
Title | Describing Reflectances for Colour Segmentation Robust to Shadows, Highlights and Textures | Type | Journal Article | ||
Year | 2011 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 33 | Issue | 5 | Pages | 917-930 |
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Abstract | The segmentation of a single material reflectance is a challenging problem due to the considerable variation in image measurements caused by the geometry of the object, shadows, and specularities. The combination of these effects has been modeled by the dichromatic reflection model. However, the application of the model to real-world images is limited due to unknown acquisition parameters and compression artifacts. In this paper, we present a robust model for the shape of a single material reflectance in histogram space. The method is based on a multilocal creaseness analysis of the histogram which results in a set of ridges representing the material reflectances. The segmentation method derived from these ridges is robust to both shadow, shading and specularities, and texture in real-world images. We further complete the method by incorporating prior knowledge from image statistics, and incorporate spatial coherence by using multiscale color contrast information. Results obtained show that our method clearly outperforms state-of-the-art segmentation methods on a widely used segmentation benchmark, having as a main characteristic its excellent performance in the presence of shadows and highlights at low computational cost. | ||||
Address | Los Alamitos; CA; USA; | ||||
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Publisher | IEEE Computer Society | Place of Publication | Editor | ||
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ISSN | 0162-8828 | ISBN | Medium | ||
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ VBW2011 | Serial | 1715 | ||
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Author | Josep Llados; Enric Marti; Juan J.Villanueva | ||||
Title | Symbol recognition by error-tolerant subgraph matching between region adjacency graphs | Type | Journal Article | ||
Year | 2001 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | |
Volume | 23 | Issue | 10 | Pages | 1137-1143 |
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Abstract | The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. | ||||
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Notes | DAG;IAM;ISE; | Approved | no | ||
Call Number | IAM @ iam @ LMV2001 | Serial | 1581 | ||
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Author | Sophie Wuerger; Kaida Xiao; Chenyang Fu; Dimosthenis Karatzas | ||||
Title | Colour-opponent mechanisms are not affected by age-related chromatic sensitivity changes | Type | Journal Article | ||
Year | 2010 | Publication | Ophthalmic and Physiological Optics | Abbreviated Journal | OPO |
Volume | 30 | Issue | 5 | Pages | 635-659 |
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Abstract | The purpose of this study was to assess whether age-related chromatic sensitivity changes are associated with corresponding changes in hue perception in a large sample of colour-normal observers over a wide age range (n = 185; age range: 18-75 years). In these observers we determined both the sensitivity along the protan, deutan and tritan line; and settings for the four unique hues, from which the characteristics of the higher-order colour mechanisms can be derived. We found a significant decrease in chromatic sensitivity due to ageing, in particular along the tritan line. From the unique hue settings we derived the cone weightings associated with the colour mechanisms that are at equilibrium for the four unique hues. We found that the relative cone weightings (w(L) /w(M) and w(L) /w(S)) associated with the unique hues were independent of age. Our results are consistent with previous findings that the unique hues are rather constant with age while chromatic sensitivity declines. They also provide evidence in favour of the hypothesis that higher-order colour mechanisms are equipped with flexible cone weightings, as opposed to fixed weights. The mechanism underlying this compensation is still poorly understood. | ||||
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Notes | DAG; IF: 1.259 | Approved | no | ||
Call Number | Admin @ si @ WXF2010 | Serial | 1826 | ||
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Author | Olivier Penacchio; C. Alejandro Parraga | ||||
Title | What is the best criterion for an efficient design of retinal photoreceptor mosaics? | Type | Journal Article | ||
Year | 2011 | Publication | Perception | Abbreviated Journal | PER |
Volume | 40 | Issue | Pages | 197 | |
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Abstract | The proportions of L, M and S photoreceptors in the primate retina are arguably determined by evolutionary pressure and the statistics of the visual environment. Two information theory-based approaches have been recently proposed for explaining the asymmetrical spatial densities of photoreceptors in humans. In the first approach Garrigan et al (2010 PLoS ONE 6 e1000677), a model for computing the information transmitted by cone arrays which considers the differential blurring produced by the long-wavelength accommodation of the eye’s lens is proposed. Their results explain the sparsity of S-cones but the optimum depends weakly on the L:M cone ratio. In the second approach (Penacchio et al, 2010 Perception 39 ECVP Supplement, 101), we show that human cone arrays make the visual representation scale-invariant, allowing the total entropy of the signal to be preserved while decreasing individual neurons’ entropy in further retinotopic representations. This criterion provides a thorough description of the distribution of L:M cone ratios and does not depend on differential blurring of the signal by the lens. Here, we investigate the similarities and differences of both approaches when applied to the same database. Our results support a 2-criteria optimization in the space of cone ratios whose components are arguably important and mostly unrelated.
[This work was partially funded by projects TIN2010-21771-C02-1 and Consolider-Ingenio 2010-CSD2007-00018 from the Spanish MICINN. CAP was funded by grant RYC-2007-00484] |
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ PeP2011a | Serial | 1719 | ||
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Author | Mikhail Mozerov; Joost Van de Weijer | ||||
Title | Global Color Sparseness and a Local Statistics Prior for Fast Bilateral Filtering | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 24 | Issue | 12 | Pages | 5842-5853 |
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Abstract | The property of smoothing while preserving edges makes the bilateral filter a very popular image processing tool. However, its non-linear nature results in a computationally costly operation. Various works propose fast approximations to the bilateral filter. However, the majority does not generalize to vector input as is the case with color images. We propose a fast approximation to the bilateral filter for color images. The filter is based on two ideas. First, the number of colors, which occur in a single natural image, is limited. We exploit this color sparseness to rewrite the initial non-linear bilateral filter as a number of linear filter operations. Second, we impose a statistical prior to the image values that are locally present within the filter window. We show that this statistical prior leads to a closed-form solution of the bilateral filter. Finally, we combine both ideas into a single fast and accurate bilateral filter for color images. Experimental results show that our bilateral filter based on the local prior yields an extremely fast bilateral filter approximation, but with limited accuracy, which has potential application in real-time video filtering. Our bilateral filter, which combines color sparseness and local statistics, yields a fast and accurate bilateral filter approximation and obtains the state-of-the-art results. | ||||
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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | LAMP; 600.079;ISE | Approved | no | ||
Call Number | Admin @ si @ MoW2015b | Serial | 2689 | ||
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Author | Santiago Segui; Laura Igual; Jordi Vitria | ||||
Title | Bagged One Class Classifiers in the Presence of Outliers | Type | Journal Article | ||
Year | 2013 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
Volume | 27 | Issue | 5 | Pages | 1350014-1350035 |
Keywords | One-class Classifier; Ensemble Methods; Bagging and Outliers | ||||
Abstract | The problem of training classifiers only with target data arises in many applications where non-target data are too costly, difficult to obtain, or not available at all. Several one-class classification methods have been presented to solve this problem, but most of the methods are highly sensitive to the presence of outliers in the target class. Ensemble methods have therefore been proposed as a powerful way to improve the classification performance of binary/multi-class learning algorithms by introducing diversity into classifiers.
However, their application to one-class classification has been rather limited. In this paper, we present a new ensemble method based on a non-parametric weighted bagging strategy for one-class classification, to improve accuracy in the presence of outliers. While the standard bagging strategy assumes a uniform data distribution, the method we propose here estimates a probability density based on a forest structure of the data. This assumption allows the estimation of data distribution from the computation of simple univariate and bivariate kernel densities. Experiments using original and noisy versions of 20 different datasets show that bagging ensemble methods applied to different one-class classifiers outperform base one-class classification methods. Moreover, we show that, in noisy versions of the datasets, the non-parametric weighted bagging strategy we propose outperforms the classical bagging strategy in a statistically significant way. |
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Notes | OR; 600.046;MV | Approved | no | ||
Call Number | Admin @ si @ SIV2013 | Serial | 2256 | ||
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Author | Arash Akbarinia; C. Alejandro Parraga | ||||
Title | Colour Constancy Beyond the Classical Receptive Field | Type | Journal Article | ||
Year | 2018 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 40 | Issue | 9 | Pages | 2081 - 2094 |
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Abstract | The problem of removing illuminant variations to preserve the colours of objects (colour constancy) has already been solved by the human brain using mechanisms that rely largely on centre-surround computations of local contrast. In this paper we adopt some of these biological solutions described by long known physiological findings into a simple, fully automatic, functional model (termed Adaptive Surround Modulation or ASM). In ASM, the size of a visual neuron's receptive field (RF) as well as the relationship with its surround varies according to the local contrast within the stimulus, which in turn determines the nature of the centre-surround normalisation of cortical neurons higher up in the processing chain. We modelled colour constancy by means of two overlapping asymmetric Gaussian kernels whose sizes are adapted based on the contrast of the surround pixels, resembling the change of RF size. We simulated the contrast-dependent surround modulation by weighting the contribution of each Gaussian according to the centre-surround contrast. In the end, we obtained an estimation of the illuminant from the set of the most activated RFs' outputs. Our results on three single-illuminant and one multi-illuminant benchmark datasets show that ASM is highly competitive against the state-of-the-art and it even outperforms learning-based algorithms in one case. Moreover, the robustness of our model is more tangible if we consider that our results were obtained using the same parameters for all datasets, that is, mimicking how the human visual system operates. These results might provide an insight on how dynamical adaptation mechanisms contribute to make object's colours appear constant to us. | ||||
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Notes | NEUROBIT; 600.068; 600.072 | Approved | no | ||
Call Number | Admin @ si @ AkP2018a | Serial | 2990 | ||
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Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
Title | Predicting Missing Ratings in Recommender Systems: Adapted Factorization Approach | Type | Journal Article | ||
Year | 2009 | Publication | International Journal of Electronic Commerce | Abbreviated Journal | |
Volume | 14 | Issue | 1 | Pages | 89-108 |
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Abstract | The paper presents a factorization-based approach to make predictions in recommender systems. These systems are widely used in electronic commerce to help customers find products according to their preferences. Taking into account the customer's ratings of some products available in the system, the recommender system tries to predict the ratings the customer would give to other products in the system. The proposed factorization-based approach uses all the information provided to compute the predicted ratings, in the same way as approaches based on Singular Value Decomposition (SVD). The main advantage of this technique versus SVD-based approaches is that it can deal with missing data. It also has a smaller computational cost. Experimental results with public data sets are provided to show that the proposed adapted factorization approach gives better predicted ratings than a widely used SVD-based approach. | ||||
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ISSN | 1086-4415 | ISBN | Medium | ||
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Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ JSL2009b | Serial | 1237 | ||
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Author | Alvaro Cepero; Albert Clapes; Sergio Escalera | ||||
Title | Automatic non-verbal communication skills analysis: a quantitative evaluation | Type | Journal Article | ||
Year | 2015 | Publication | AI Communications | Abbreviated Journal | AIC |
Volume | 28 | Issue | 1 | Pages | 87-101 |
Keywords | Social signal processing; human behavior analysis; multi-modal data description; multi-modal data fusion; non-verbal communication analysis; e-Learning | ||||
Abstract | The oral communication competence is defined on the top of the most relevant skills for one's professional and personal life. Because of the importance of communication in our activities of daily living, it is crucial to study methods to evaluate and provide the necessary feedback that can be used in order to improve these communication capabilities and, therefore, learn how to express ourselves better. In this work, we propose a system capable of evaluating quantitatively the quality of oral presentations in an automatic fashion. The system is based on a multi-modal RGB, depth, and audio data description and a fusion approach in order to recognize behavioral cues and train classifiers able to eventually predict communication quality levels. The performance of the proposed system is tested on a novel dataset containing Bachelor thesis' real defenses, presentations from an 8th semester Bachelor courses, and Master courses' presentations at Universitat de Barcelona. Using as groundtruth the marks assigned by actual instructors, our system achieves high performance categorizing and ranking presentations by their quality, and also making real-valued mark predictions. | ||||
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ISSN | 0921-7126 | ISBN | Medium | ||
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Notes | HUPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ CCE2015 | Serial | 2549 | ||
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Author | David Roche; Debora Gil; Jesus Giraldo | ||||
Title | Multiple active receptor conformation, agonist efficacy and maximum effect of the system: the conformation-based operational model of agonism, | Type | Journal Article | ||
Year | 2013 | Publication | Drug Discovery Today | Abbreviated Journal | DDT |
Volume | 18 | Issue | 7-8 | Pages | 365-371 |
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Abstract | The operational model of agonism assumes that the maximum effect a particular receptor system can achieve (the Em parameter) is fixed. Em estimates are above but close to the asymptotic maximum effects of endogenous agonists. The concept of Em is contradicted by superagonists and those positive allosteric modulators that significantly increase the maximum effect of endogenous agonists. An extension of the operational model is proposed that assumes that the Em parameter does not necessarily have a single value for a receptor system but has multiple values associated to multiple active receptor conformations. The model provides a mechanistic link between active receptor conformation and agonist efficacy, which can be useful for the analysis of agonist response under different receptor scenarios. | ||||
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Publisher | Elsevier | Place of Publication | Editor | ||
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Notes | IAM; 600.057; 600.054 | Approved | no | ||
Call Number | IAM @ iam @ RGG2013a | Serial | 2190 | ||
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