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Author | Gabriel Villalonga; Sebastian Ramos; German Ros; David Vazquez; Antonio Lopez | ||||
Title | 3d Pedestrian Detection via Random Forest | Type | Miscellaneous | ||
Year | 2014 | Publication | European Conference on Computer Vision | Abbreviated Journal | |
Volume | Issue | Pages | 231-238 | ||
Keywords | Pedestrian Detection | ||||
Abstract | Our demo focuses on showing the extraordinary performance of our novel 3D pedestrian detector along with its simplicity and real-time capabilities. This detector has been designed for autonomous driving applications, but it can also be applied in other scenarios that cover both outdoor and indoor applications.
Our pedestrian detector is based on the combination of a random forest classifier with HOG-LBP features and the inclusion of a preprocessing stage based on 3D scene information in order to precisely determinate the image regions where the detector should search for pedestrians. This approach ends up in a high accurate system that runs real-time as it is required by many computer vision and robotics applications. |
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Address | Zurich; suiza; September 2014 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ECCV-Demo | ||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ VRR2014 | Serial | 2570 | ||
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Author | Salvatore Tabbone; Oriol Ramos Terrades | ||||
Title | An Overview of Symbol Recognition | Type | Book Chapter | ||
Year | 2014 | Publication | Handbook of Document Image Processing and Recognition | Abbreviated Journal | |
Volume | D | Issue | Pages | 523-551 | |
Keywords | Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting | ||||
Abstract | According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity. | ||||
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Publisher | Springer London | Place of Publication | Editor | D. Doermann; K. Tombre | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-0-85729-858-4 | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ TaT2014 | Serial | 2489 | ||
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Author | Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen | ||||
Title | Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging | Type | Conference Article | ||
Year | 2014 | Publication | 17th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
Volume | 8896 | Issue | Pages | 231-238 | |
Keywords | Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging | ||||
Abstract | Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across dierent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three dierent OF methods, including HARP. |
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Address | Boston; USA; September 2014 | ||||
Corporate Author | Thesis | ||||
Publisher | Springer International Publishing | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-319-14677-5 | Medium | |
Area | Expedition | Conference | STACOM | ||
Notes | IAM; ADAS; 600.060; 601.145; 600.076; 600.075 | Approved | no | ||
Call Number | Admin @ si @ MKF2014 | Serial | 2495 | ||
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Author | Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate | ||||
Title | Local Analysis of Confidence Measures for Optical Flow Quality Evaluation | Type | Conference Article | ||
Year | 2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | 3 | Issue | Pages | 450-457 | |
Keywords | Optical Flow; Confidence Measure; Performance Evaluation. | ||||
Abstract | Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance. |
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Address | Lisboa; January 2014 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | VISAPP | ||
Notes | IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 | Approved | no | ||
Call Number | Admin @ si @ MGM2014 | Serial | 2432 | ||
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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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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | MILAB; 605.203 | Approved | no | ||
Call Number | Admin @ si @ CPR2014a | Serial | 2469 | ||
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Author | Lorenzo Seidenari; Giuseppe Serra; Andrew Bagdanov; Alberto del Bimbo | ||||
Title | Local pyramidal descriptors for image recognition | Type | Journal Article | ||
Year | 2014 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 36 | Issue | 5 | Pages | 1033 - 1040 |
Keywords | Object categorization; local features; kernel methods | ||||
Abstract | In this paper we present a novel method to improve the flexibility of descriptor matching for image recognition by using local multiresolution
pyramids in feature space. We propose that image patches be represented at multiple levels of descriptor detail and that these levels be defined in terms of local spatial pooling resolution. Preserving multiple levels of detail in local descriptors is a way of hedging one’s bets on which levels will most relevant for matching during learning and recognition. We introduce the Pyramid SIFT (P-SIFT) descriptor and show that its use in four state-of-the-art image recognition pipelines improves accuracy and yields state-of-the-art results. Our technique is applicable independently of spatial pyramid matching and we show that spatial pyramids can be combined with local pyramids to obtain further improvement.We achieve state-of-the-art results on Caltech-101 (80.1%) and Caltech-256 (52.6%) when compared to other approaches based on SIFT features over intensity images. Our technique is efficient and is extremely easy to integrate into image recognition pipelines. |
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Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 0162-8828 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @ SSB2014 | Serial | 2524 | ||
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Author | Cristhian A. Aguilera-Carrasco | ||||
Title | Evaluation of feature detectors and descriptors in VISIBLE-LWIR cross-spectral imaging | Type | Report | ||
Year | 2014 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 177 | Issue | Pages | ||
Keywords | Multi-spectral; Cross-spectral; Visible-LWIR imaging; Multimodal. | ||||
Abstract | This thesis evaluates the performance of different state-of-art feature detectors and descriptors algorithms in the Visible-LWIR cross-spectral scenario. The focus is to determine if current detector and descriptor algorithms can be used to match features between the LWIR spectrum and the visible spectrum in applications such as, visual odometry, object recognition, image registration and stereo vision. An outdoor cross-spectral dataset was created to evaluate the suitability of the different algorithms. The results
show that the tested algorithms are not suitable to the task of matching features across different spectra. The repeatability ratio was smaller than the 30 percent in the best case and in general matched features were not accurate located. Additionally, these results also suggest that is necessary to create new algorithms that take into account the nature of the different spectra, describing characteristics that exist in both spectra such as discontinuities. |
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Corporate Author | Thesis | Master's thesis | |||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @Agu2014 | Serial | 2526 | ||
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Author | Oualid M. Benkarim; Petia Radeva; Laura Igual | ||||
Title | Label Consistent Multiclass Discriminative Dictionary Learning for MRI Segmentation | Type | Conference Article | ||
Year | 2014 | Publication | 8th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
Volume | 8563 | Issue | Pages | 138-147 | |
Keywords | MRI segmentation; sparse representation; discriminative dic- tionary learning; multiclass classication | ||||
Abstract | The automatic segmentation of multiple subcortical structures in brain Magnetic Resonance Images (MRI) still remains a challenging task. In this paper, we address this problem using sparse representation and discriminative dictionary learning, which have shown promising results in compression, image denoising and recently in MRI segmentation. Particularly, we use multiclass dictionaries learned from a set of brain atlases to simultaneously segment multiple subcortical structures.
We also impose dictionary atoms to be specialized in one given class using label consistent K-SVD, which can alleviate the bias produced by unbalanced libraries, present when dealing with small structures. The proposed method is compared with other state of the art approaches for the segmentation of the Basal Ganglia of 35 subjects of a public dataset. The promising results of the segmentation method show the eciency of the multiclass discriminative dictionary learning algorithms in MRI segmentation problems. |
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Address | Palma de Mallorca; July 2014 | ||||
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Publisher | Springer International Publishing | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-319-08848-8 | Medium | |
Area | Expedition | Conference | AMDO | ||
Notes | MILAB; OR | Approved | no | ||
Call Number | Admin @ si @ BRI2014 | Serial | 2494 | ||
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Author | Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier | ||||
Title | Normalisation et validation d'images de documents capturées en mobilité | Type | Conference Article | ||
Year | 2014 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
Volume | Issue | Pages | 109-124 | ||
Keywords | mobile document image acquisition; perspective correction; illumination correction; quality assessment; focus measure; OCR accuracy prediction | ||||
Abstract | Mobile document image acquisition integrates many distortions which must be corrected or detected on the device, before the document becomes unavailable or paying data transmission fees. In this paper, we propose a system to correct perspective and illumination issues, and estimate the sharpness of the image for OCR recognition. The correction step relies on fast and accurate border detection followed by illumination normalization. Its evaluation on a private dataset shows a clear improvement on OCR accuracy. The quality assessment
step relies on a combination of focus measures. Its evaluation on a public dataset shows that this simple method compares well to state of the art, learning-based methods which cannot be embedded on a mobile, and outperforms metric-based methods. |
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Address | Nancy; France; March 2014 | ||||
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Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CIFED | ||
Notes | DAG; 601.223; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RCO2014b | Serial | 2546 | ||
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Author | Frederic Sampedro; Sergio Escalera; Anna Puig | ||||
Title | Iterative Multiclass Multiscale Stacked Sequential Learning: definition and application to medical volume segmentation | Type | Journal Article | ||
Year | 2014 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 46 | Issue | Pages | 1-10 | |
Keywords | Machine learning; Sequential learning; Multi-class problems; Contextual learning; Medical volume segmentation | ||||
Abstract | In this work we present the iterative multi-class multi-scale stacked sequential learning framework (IMMSSL), a novel learning scheme that is particularly suited for medical volume segmentation applications. This model exploits the inherent voxel contextual information of the structures of interest in order to improve its segmentation performance results. Without any feature set or learning algorithm prior assumption, the proposed scheme directly seeks to learn the contextual properties of a region from the predicted classifications of previous classifiers within an iterative scheme. Performance results regarding segmentation accuracy in three two-class and multi-class medical volume datasets show a significant improvement with respect to state of the art alternatives. Due to its easiness of implementation and its independence of feature space and learning algorithm, the presented machine learning framework could be taken into consideration as a first choice in complex volume segmentation scenarios. | ||||
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Area | Expedition | Conference | |||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ SEP2014 | Serial | 2550 | ||
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Author | A.Kesidis; Dimosthenis Karatzas | ||||
Title | Logo and Trademark Recognition | Type | Book Chapter | ||
Year | 2014 | Publication | Handbook of Document Image Processing and Recognition | Abbreviated Journal | |
Volume | D | Issue | Pages | 591-646 | |
Keywords | Logo recognition; Logo removal; Logo spotting; Trademark registration; Trademark retrieval systems | ||||
Abstract | The importance of logos and trademarks in nowadays society is indisputable, variably seen under a positive light as a valuable service for consumers or a negative one as a catalyst of ever-increasing consumerism. This chapter discusses the technical approaches for enabling machines to work with logos, looking into the latest methodologies for logo detection, localization, representation, recognition, retrieval, and spotting in a variety of media. This analysis is presented in the context of three different applications covering the complete depth and breadth of state of the art techniques. These are trademark retrieval systems, logo recognition in document images, and logo detection and removal in images and videos. This chapter, due to the very nature of logos and trademarks, brings together various facets of document image analysis spanning graphical and textual content, while it links document image analysis to other computer vision domains, especially when it comes to the analysis of real-scene videos and images. | ||||
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Publisher | Springer London | Place of Publication | Editor | D. Doermann; K. Tombre | |
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-0-85729-858-4 | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ KeK2014 | Serial | 2425 | ||
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Author | David Fernandez; Pau Riba; Alicia Fornes; Josep Llados | ||||
Title | On the Influence of Key Point Encoding for Handwritten Word Spotting | Type | Conference Article | ||
Year | 2014 | Publication | 14th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 476 - 481 | ||
Keywords | Local descriptors; Interest points; Handwritten documents; Word spotting; Historical document analysis | ||||
Abstract | In this paper we evaluate the influence of the selection of key points and the associated features in the performance of word spotting processes. In general, features can be extracted from a number of characteristic points like corners, contours, skeletons, maxima, minima, crossings, etc. A number of descriptors exist in the literature using different interest point detectors. But the intrinsic variability of handwriting vary strongly on the performance if the interest points are not stable enough. In this paper, we analyze the performance of different descriptors for local interest points. As benchmarking dataset we have used the Barcelona Marriage Database that contains handwritten records of marriages over five centuries. | ||||
Address | Creete Island; Grecia; September 2014 | ||||
Corporate Author | Thesis | ||||
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Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 2167-6445 | ISBN | 978-1-4799-4335-7 | Medium | |
Area | Expedition | Conference | ICFHR | ||
Notes | DAG; 600.056; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FRF2014 | Serial | 2460 | ||
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Author | David Roche; Debora Gil; Jesus Giraldo | ||||
Title | Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models? | Type | Book Chapter | ||
Year | 2014 | Publication | G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology | Abbreviated Journal | |
Volume | 796 | Issue | 3 | Pages | 159-181 |
Keywords | β-arrestin; biased agonism; curve fitting; empirical modeling; evolutionary algorithm; functional selectivity; G protein; GPCR; Hill coefficient; intrinsic efficacy; inverse agonism; mathematical modeling; mechanistic modeling; operational model; parameter optimization; receptor dimer; receptor oligomerization; receptor constitutive activity; signal transduction; two-state model | ||||
Abstract | Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists. | ||||
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Publisher | Springer Netherlands | Place of Publication | Editor | ||
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ISSN | 0065-2598 | ISBN | 978-94-007-7422-3 | Medium | |
Area | Expedition | Conference | |||
Notes | IAM; 600.075 | Approved | no | ||
Call Number | IAM @ iam @ RGG2014 | Serial | 2197 | ||
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Author | Simone Balocco; Carlo Gatta; Francesco Ciompi; A. Wahle; Petia Radeva; S. Carlier; G. Unal; E. Sanidas; J. Mauri; X. Carillo; T. Kovarnik; C. Wang; H. Chen; T. P. Exarchos; D. I. Fotiadis; F. Destrempes; G. Cloutier; Oriol Pujol; Marina Alberti; E. G. Mendizabal-Ruiz; M. Rivera; T. Aksoy; R. W. Downe; I. A. Kakadiaris | ||||
Title | Standardized evaluation methodology and reference database for evaluating IVUS image segmentation | Type | Journal Article | ||
Year | 2014 | Publication | Computerized Medical Imaging and Graphics | Abbreviated Journal | CMIG |
Volume | 38 | Issue | 2 | Pages | 70-90 |
Keywords | IVUS (intravascular ultrasound); Evaluation framework; Algorithm comparison; Image segmentation | ||||
Abstract | This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated.
We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved. |
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Notes | MILAB; LAMP; HuPBA; 600.046; 600.063; 600.079 | Approved | no | ||
Call Number | Admin @ si @ BGC2013 | Serial | 2314 | ||
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Author | P. Ricaurte; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa | ||||
Title | Performance Evaluation of Feature Point Descriptors in the Infrared Domain | Type | Conference Article | ||
Year | 2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | 1 | Issue | Pages | 545-550 | |
Keywords | Infrared Imaging; Feature Point Descriptors | ||||
Abstract | This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered. | ||||
Address | Lisboa; Portugal; January 2014 | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | VISAPP | ||
Notes | ADAS; 600.055; 600.076 | Approved | no | ||
Call Number | Admin @ si @ RCA2014b | Serial | 2476 | ||
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