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Author | Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez | ||||
Title | Video Alignment for Change Detection | Type | Journal Article | ||
Year | 2011 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 20 | Issue | 7 | Pages | 1858-1869 |
Keywords | video alignment | ||||
Abstract | In this work, we address the problem of aligning two video sequences. Such alignment refers to synchronization, i.e., the establishment of temporal correspondence between frames of the first and second video, followed by spatial registration of all the temporally corresponding frames. Video synchronization and alignment have been attempted before, but most often in the relatively simple cases of fixed or rigidly attached cameras and simultaneous acquisition. In addition, restrictive assumptions have been applied, including linear time correspondence or the knowledge of the complete trajectories of corresponding scene points; to some extent, these assumptions limit the practical applicability of any solutions developed. We intend to solve the more general problem of aligning video sequences recorded by independently moving cameras that follow similar trajectories, based only on the fusion of image intensity and GPS information. The novelty of our approach is to pose the synchronization as a MAP inference problem on a Bayesian network including the observations from these two sensor types, which have been proved complementary. Alignment results are presented in the context of videos recorded from vehicles driving along the same track at different times, for different road types. In addition, we explore two applications of the proposed video alignment method, both based on change detection between aligned videos. One is the detection of vehicles, which could be of use in ADAS. The other is online difference spotting videos of surveillance rounds. | ||||
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Notes | ADAS; IF | Approved | no | ||
Call Number | DPS 2011; ADAS @ adas @ dps2011 | Serial ![]() |
1705 | ||
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Author | Pierluigi Casale; Oriol Pujol; Petia Radeva | ||||
Title | Personalization and User Verification in Wearable Systems using Biometric Walking Patterns | Type | Journal Article | ||
Year | 2012 | Publication | Personal and Ubiquitous Computing | Abbreviated Journal | PUC |
Volume | 16 | Issue | 5 | Pages | 563-580 |
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Abstract | In this article, a novel technique for user’s authentication and verification using gait as a biometric unobtrusive pattern is proposed. The method is based on a two stages pipeline. First, a general activity recognition classifier is personalized for an specific user using a small sample of her/his walking pattern. As a result, the system is much more selective with respect to the new walking pattern. A second stage verifies whether the user is an authorized one or not. This stage is defined as a one-class classification problem. In order to solve this problem, a four-layer architecture is built around the geometric concept of convex hull. This architecture allows to improve robustness to outliers, modeling non-convex shapes, and to take into account temporal coherence information. Two different scenarios are proposed as validation with two different wearable systems. First, a custom high-performance wearable system is built and used in a free environment. A second dataset is acquired from an Android-based commercial device in a ‘wild’ scenario with rough terrains, adversarial conditions, crowded places and obstacles. Results on both systems and datasets are very promising, reducing the verification error rates by an order of magnitude with respect to the state-of-the-art technologies. | ||||
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Publisher | Springer-Verlag | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 1617-4909 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ CPR2012 | Serial ![]() |
1706 | ||
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Author | Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Xavier Roca | ||||
Title | Efficient Discriminative Multiresolution Cascade for Real-Time Human Detection Applications | Type | Journal Article | ||
Year | 2011 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 32 | Issue | 13 | Pages | 1581-1587 |
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Abstract | Human detection is fundamental in many machine vision applications, like video surveillance, driving assistance, action recognition and scene understanding. However in most of these applications real-time performance is necessary and this is not achieved yet by current detection methods.
This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a linear Support Vector Machine (SVM) composed of HOG features at different resolutions, from coarse at the first level to fine at the last one. In contrast to previous methods, our approach uses a non-uniform stride of the sliding window that is defined by the feature resolution and allows the detection to be incrementally refined as going from coarse-to-fine resolution. In this way, the speed-up of the cascade is not only due to the fewer number of features computed at the first levels of the cascade, but also to the reduced number of windows that need to be evaluated at the coarse resolution. Experimental results show that our method reaches a detection rate comparable with the state-of-the-art of detectors based on HOG features, while at the same time the detection search is up to 23 times faster. |
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Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ PGB2011a | Serial ![]() |
1707 | ||
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Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
Title | Rank Estimation in Missing Data Matrix Problems | Type | Journal Article | ||
Year | 2011 | Publication | Journal of Mathematical Imaging and Vision | Abbreviated Journal | JMIV |
Volume | 39 | Issue | 2 | Pages | 140-160 |
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Abstract | A novel technique for missing data matrix rank estimation is presented. It is focused on matrices of trajectories, where every element of the matrix corresponds to an image coordinate from a feature point of a rigid moving object at a given frame; missing data are represented as empty entries. The objective of the proposed approach is to estimate the rank of a missing data matrix in order to fill in empty entries with some matrix completion method, without using or assuming neither the number of objects contained in the scene nor the kind of their motion. The key point of the proposed technique consists in studying the frequency behaviour of the individual trajectories, which are seen as 1D signals. The main assumption is that due to the rigidity of the moving objects, the frequency content of the trajectories will be similar after filling in their missing entries. The proposed rank estimation approach can be used in different computer vision problems, where the rank of a missing data matrix needs to be estimated. Experimental results with synthetic and real data are provided in order to empirically show the good performance of the proposed approach. | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | 0924-9907 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ JSL2011; | Serial ![]() |
1710 | ||
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Author | Carme Julia; Felipe Lumbreras; Angel Sappa | ||||
Title | A Factorization-based Approach to Photometric Stereo | Type | Journal Article | ||
Year | 2011 | Publication | International Journal of Imaging Systems and Technology | Abbreviated Journal | IJIST |
Volume | 21 | Issue | 1 | Pages | 115-119 |
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Abstract | This article presents an adaptation of a factorization technique to tackle the photometric stereo problem. That is to recover the surface normals and reflectance of an object from a set of images obtained under different lighting conditions. The main contribution of the proposed approach is to consider pixels in shadow and saturated regions as missing data, in order to reduce their influence to the result. Concretely, an adapted Alternation technique is used to deal with missing data. Experimental results considering both synthetic and real images show the viability of the proposed factorization-based strategy. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 115–119, 2011. | ||||
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Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ JLS2011; ADAS @ adas @ | Serial ![]() |
1711 | ||
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Author | Jose Seabra; Francesco Ciompi; Oriol Pujol; J. Mauri; Petia Radeva; Joao Sanchez | ||||
Title | Rayleigh Mixture Model for Plaque Characterization in Intravascular Ultrasound | Type | Journal Article | ||
Year | 2011 | Publication | IEEE Transactions on Biomedical Engineering | Abbreviated Journal | TBME |
Volume | 58 | Issue | 5 | Pages | 1314-1324 |
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Abstract | Vulnerable plaques are the major cause of carotid and coronary vascular problems, such as heart attack or stroke. A correct modeling of plaque echomorphology and composition can help the identification of such lesions. The Rayleigh distribution is widely used to describe (nearly) homogeneous areas in ultrasound images. Since plaques may contain tissues with heterogeneous regions, more complex distributions depending on multiple parameters are usually needed, such as Rice, K or Nakagami distributions. In such cases, the problem formulation becomes more complex, and the optimization procedure to estimate the plaque echomorphology is more difficult. Here, we propose to model the tissue echomorphology by means of a mixture of Rayleigh distributions, known as the Rayleigh mixture model (RMM). The problem formulation is still simple, but its ability to describe complex textural patterns is very powerful. In this paper, we present a method for the automatic estimation of the RMM mixture parameters by means of the expectation maximization algorithm, which aims at characterizing tissue echomorphology in ultrasound (US). The performance of the proposed model is evaluated with a database of in vitro intravascular US cases. We show that the mixture coefficients and Rayleigh parameters explicitly derived from the mixture model are able to accurately describe different plaque types and to significantly improve the characterization performance of an already existing methodology. | ||||
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Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ SCP2011 | Serial ![]() |
1712 | ||
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Author | Maria Salamo; Sergio Escalera | ||||
Title | Increasing Retrieval Quality in Conversational Recommenders | Type | Journal Article | ||
Year | 2011 | Publication | IEEE Transactions on Knowledge and Data Engineering | Abbreviated Journal | TKDE |
Volume | 99 | Issue | Pages | 1-1 | |
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Abstract | IF JCR CCIA 2.286 2009 24/103
JCR Impact Factor 2010: 1.851 A major task of research in conversational recommender systems is personalization. Critiquing is a common and powerful form of feedback, where a user can express her feature preferences by applying a series of directional critiques over the recommendations instead of providing specific preference values. Incremental Critiquing is a conversational recommender system that uses critiquing as a feedback to efficiently personalize products. The expectation is that in each cycle the system retrieves the products that best satisfy the user’s soft product preferences from a minimal information input. In this paper, we present a novel technique that increases retrieval quality based on a combination of compatibility and similarity scores. Under the hypothesis that a user learns Turing the recommendation process, we propose two novel exponential reinforcement learning approaches for compatibility that take into account both the instant at which the user makes a critique and the number of satisfied critiques. Moreover, we consider that the impact of features on the similarity differs according to the preferences manifested by the user. We propose a global weighting approach that uses a common weight for nearest cases in order to focus on groups of relevant products. We show that our methodology significantly improves recommendation efficiency in four data sets of different sizes in terms of session length in comparison with state-of-the-art approaches. Moreover, our recommender shows higher robustness against noisy user data when compared to classical approaches |
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Publisher | IEEE | Place of Publication | Editor | ||
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Series Volume | Series Issue | Edition | |||
ISSN | 1041-4347 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | MILAB; HuPBA | Approved | no | ||
Call Number | Admin @ si @ SaE2011 | Serial ![]() |
1713 | ||
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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 | |||
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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 | 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 | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 0162-8828 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ VBW2011 | Serial ![]() |
1715 | ||
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Author | Ariel Amato; Mikhail Mozerov; Andrew Bagdanov; Jordi Gonzalez | ||||
Title | Accurate Moving Cast Shadow Suppression Based on Local Color Constancy detection | Type | Journal Article | ||
Year | 2011 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 20 | Issue | 10 | Pages | 2954 - 2966 |
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Abstract | This paper describes a novel framework for detection and suppression of properly shadowed regions for most possible scenarios occurring in real video sequences. Our approach requires no prior knowledge about the scene, nor is it restricted to specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene, the values of the background image are divided by values of the current frame in the RGB color space. We show how this luminance ratio can be used to identify segments with low gradient constancy, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of our method compared with the most sophisticated, state-of-the-art shadow detection algorithms. These results show that our approach is robust and accurate over a broad range of shadow types and challenging video conditions. | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | 1057-7149 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ AMB2011 | Serial ![]() |
1716 | ||
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Author | Arjan Gijsenij; Theo Gevers; Joost Van de Weijer | ||||
Title | Computational Color Constancy: Survey and Experiments | Type | Journal Article | ||
Year | 2011 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 20 | Issue | 9 | Pages | 2475-2489 |
Keywords | computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting | ||||
Abstract | Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets. | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | 1057-7149 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ISE;CIC | Approved | no | ||
Call Number | Admin @ si @ GGW2011 | Serial ![]() |
1717 | ||
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Author | Xavier Boix; Josep M. Gonfaus; Joost Van de Weijer; Andrew Bagdanov; Joan Serrat; Jordi Gonzalez | ||||
Title | Harmony Potentials: Fusing Global and Local Scale for Semantic Image Segmentation | Type | Journal Article | ||
Year | 2012 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
Volume | 96 | Issue | 1 | Pages | 83-102 |
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Abstract | The Hierarchical Conditional Random Field(HCRF) model have been successfully applied to a number of image labeling problems, including image segmentation. However, existing HCRF models of image segmentation do not allow multiple classes to be assigned to a single region, which limits their ability to incorporate contextual information across multiple scales.
At higher scales in the image, this representation yields an oversimplied model since multiple classes can be reasonably expected to appear within large regions. This simplied model particularly limits the impact of information at higher scales. Since class-label information at these scales is usually more reliable than at lower, noisier scales, neglecting this information is undesirable. To address these issues, we propose a new consistency potential for image labeling problems, which we call the harmony potential. It can encode any possible combi- nation of labels, penalizing only unlikely combinations of classes. We also propose an eective sampling strategy over this expanded label set that renders tractable the underlying optimization problem. Our approach obtains state-of-the-art results on two challenging, standard benchmark datasets for semantic image segmentation: PASCAL VOC 2010, and MSRC-21. |
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Series Volume | Series Issue | Edition | |||
ISSN | 0920-5691 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ISE;CIC;ADAS | Approved | no | ||
Call Number | Admin @ si @ BGW2012 | Serial ![]() |
1718 | ||
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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 | C. Alejandro Parraga; Olivier Penacchio; Maria Vanrell | ||||
Title | Retinal Filtering Matches Natural Image Statistics at Low Luminance Levels | Type | Journal Article | ||
Year | 2011 | Publication | Perception | Abbreviated Journal | PER |
Volume | 40 | Issue | Pages | 96 | |
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Abstract | The assumption that the retina’s main objective is to provide a minimum entropy representation to higher visual areas (ie efficient coding principle) allows to predict retinal filtering in space–time and colour (Atick, 1992 Network 3 213–251). This is achieved by considering the power spectra of natural images (which is proportional to 1/f2) and the suppression of retinal and image noise. However, most studies consider images within a limited range of lighting conditions (eg near noon) whereas the visual system’s spatial filtering depends on light intensity and the spatiochromatic properties of natural scenes depend of the time of the day. Here, we explore whether the dependence of visual spatial filtering on luminance match the changes in power spectrum of natural scenes at different times of the day. Using human cone-activation based naturalistic stimuli (from the Barcelona Calibrated Images Database), we show that for a range of luminance levels, the shape of the retinal CSF reflects the slope of the power spectrum at low spatial frequencies. Accordingly, the retina implements the filtering which best decorrelates the input signal at every luminance level. This result is in line with the body of work that places efficient coding as a guiding neural principle. | ||||
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ PPV2011 | Serial ![]() |
1720 | ||
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Author | Olivier Penacchio | ||||
Title | Mixed Hodge Structures and Equivariant Sheaves on the Projective Plane | Type | Journal Article | ||
Year | 2011 | Publication | Mathematische Nachrichten | Abbreviated Journal | MN |
Volume | 284 | Issue | 4 | Pages | 526-542 |
Keywords | Mixed Hodge structures, equivariant sheaves, MSC (2010) Primary: 14C30, Secondary: 14F05, 14M25 | ||||
Abstract | We describe an equivalence of categories between the category of mixed Hodge structures and a category of equivariant vector bundles on a toric model of the complex projective plane which verify some semistability condition. We then apply this correspondence to define an invariant which generalizes the notion of R-split mixed Hodge structure and give calculations for the first group of cohomology of possibly non smooth or non-complete curves of genus 0 and 1. Finally, we describe some extension groups of mixed Hodge structures in terms of equivariant extensions of coherent sheaves. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim | ||||
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Publisher | WILEY-VCH Verlag | Place of Publication | Editor | R. Mennicken | |
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Series Volume | Series Issue | Edition | |||
ISSN | 1522-2616 | ISBN | Medium | ||
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ Pen2011 | Serial ![]() |
1721 | ||
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