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| Author | Marcel P. Lucassen; Theo Gevers; Arjan Gijsenij | ||||
| Title | Texture Affects Color Emotion | Type | Journal Article | ||
| Year | 2011 | Publication | Color Research & Applications | Abbreviated Journal | CRA |
| Volume | 36 | Issue | 6 | Pages  |
426–436 |
| Keywords | color;texture;color emotion;observer variability;ranking | ||||
| Abstract | Several studies have recorded color emotions in subjects viewing uniform color (UC) samples. We conduct an experiment to measure and model how these color emotions change when texture is added to the color samples. Using a computer monitor, our subjects arrange samples along four scales: warm–cool, masculine–feminine, hard–soft, and heavy–light. Three sample types of increasing visual complexity are used: UC, grayscale textures, and color textures (CTs). To assess the intraobserver variability, the experiment is repeated after 1 week. Our results show that texture fully determines the responses on the Hard-Soft scale, and plays a role of decreasing weight for the masculine–feminine, heavy–light, and warm–cool scales. Using some 25,000 observer responses, we derive color emotion functions that predict the group-averaged scale responses from the samples' color and texture parameters. For UC samples, the accuracy of our functions is significantly higher (average R2 = 0.88) than that of previously reported functions applied to our data. The functions derived for CT samples have an accuracy of R2 = 0.80. We conclude that when textured samples are used in color emotion studies, the psychological responses may be strongly affected by texture. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010 | ||||
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| Area | Expedition | Conference | |||
| Notes | ALTRES;ISE | Approved | no | ||
| Call Number | Admin @ si @ LGG2011 | Serial | 1844 | ||
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| Author | Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga | ||||
| Title | Saliency Estimation Using a Non-Parametric Low-Level Vision Model | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages |
433-440 | ||
| Keywords | Gaussian mixture model;ad hoc parameter selection;center-surround inhibition windows;center-surround mechanism;color appearance model;convolution;eye-fixation data;human vision;innate spatial pooling mechanism;inverse wavelet transform;low-level visual front-end;nonparametric low-level vision model;saliency estimation;saliency map;scale integration;scale-weighted center-surround response;scale-weighting function;visual task;Gaussian processes;biology;biology computing;colour vision;computer vision;visual perception;wavelet transforms | ||||
| Abstract | Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to construct a saliency map. However, integrating spatial information and justifying the choice of various parameter values remain open problems. In this paper we show that an efficient model of color appearance in human vision, which contains a principled selection of parameters as well as an innate spatial pooling mechanism, can be generalized to obtain a saliency model that outperforms state-of-the-art models. Scale integration is achieved by an inverse wavelet transform over the set of scale-weighted center-surround responses. The scale-weighting function (termed ECSF) has been optimized to better replicate psychophysical data on color appearance, and the appropriate sizes of the center-surround inhibition windows have been determined by training a Gaussian Mixture Model on eye-fixation data, thus avoiding ad-hoc parameter selection. Additionally, we conclude that the extension of a color appearance model to saliency estimation adds to the evidence for a common low-level visual front-end for different visual tasks. | ||||
| Address | Colorado Springs | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1063-6919 | ISBN | 978-1-4577-0394-2 | Medium | |
| Area | Expedition | Conference | CVPR | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MVO2011 | Serial | 1757 | ||
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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 | Muhammad Anwer Rao; David Vazquez; Antonio Lopez | ||||
| Title | Color Contribution to Part-Based Person Detection in Different Types of Scenarios | Type | Conference Article | ||
| Year | 2011 | Publication | 14th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
| Volume | 6855 | Issue | II | Pages |
463-470 |
| Keywords | Pedestrian Detection; Color | ||||
| Abstract | Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution. | ||||
| Address | Seville, Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer | Place of Publication | Berlin Heidelberg | Editor | P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
| Language | English | Summary Language | english | Original Title | Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-23677-8 | Medium | |
| Area | Expedition | Conference | CAIP | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ RVL2011b | Serial | 1665 | ||
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| Author | Jaime Moreno; Xavier Otazu | ||||
| Title | Image coder based on Hilbert scanning of embedded quadTrees | Type | Conference Article | ||
| Year | 2011 | Publication | Data Compression Conference | Abbreviated Journal | |
| Volume | Issue | Pages |
470-470 | ||
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| Abstract | In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | DCC | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MoO2011b | Serial | 2177 | ||
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| Author | Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin Yuste; Petia Radeva | ||||
| Title | Accurate and Robust Fully-Automatic QCA: Method and Numerical Validation | Type | Conference Article | ||
| Year | 2011 | Publication | 14th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
| Volume | 14 | Issue | 3 | Pages |
496-503 |
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| Abstract | The Quantitative Coronary Angiography (QCA) is a methodology used to evaluate the arterial diseases and, in particular, the degree of stenosis. In this paper we propose AQCA, a fully automatic method for vessel segmentation based on graph cut theory. Vesselness, geodesic paths and a new multi-scale edgeness map are used to compute a globally optimal artery segmentation. We evaluate the method performance in a rigorous numerical way on two datasets. The method can detect an artery with precision 92.9 +/- 5% and sensitivity 94.2 +/- 6%. The average absolute distance error between detected and ground truth centerline is 1.13 +/- 0.11 pixels (about 0.27 +/- 0.025 mm) and the absolute relative error in the vessel caliber estimation is 2.93% with almost no bias. Moreover, the method can discriminate between arteries and catheter with an accuracy of 96.4%. | ||||
| Address | Toronto, Canada | ||||
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| Publisher | Springer | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | 978-3-642-23625-9 | Medium | ||
| Area | Expedition | Conference | MICCAI | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ HGE2011 | Serial | 1769 | ||
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| Author | Sergio Escalera; Alicia Fornes; Oriol Pujol; Josep Llados; Petia Radeva | ||||
| Title | Circular Blurred Shape Model for Multiclass Symbol Recognition | Type | Journal Article | ||
| Year | 2011 | Publication | IEEE Transactions on Systems, Man and Cybernetics (Part B) (IEEE) | Abbreviated Journal | TSMCB |
| Volume | 41 | Issue | 2 | Pages |
497-506 |
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| Abstract | In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations. | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1083-4419 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB; DAG;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ EFP2011 | Serial | 1784 | ||
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| Author | Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie | ||||
| Title | Inferring the Performance of Medical Imaging Algorithms | Type | Conference Article | ||
| Year | 2011 | Publication | 14th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
| Volume | 6854 | Issue | Pages |
520-528 | |
| Keywords | Validation, Statistical Inference, Medical Imaging Algorithms. | ||||
| Abstract | Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence. |
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| Address | Sevilla | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer-Verlag Berlin Heidelberg | Place of Publication | Berlin | Editor | Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | L | Abbreviated Series Title | LNCS | |
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CAIP | ||
| Notes | IAM; ADAS | Approved | no | ||
| Call Number | IAM @ iam @ HGR2011 | Serial | 1676 | ||
| Permanent link to this record | |||||
| 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 | |
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1522-2616 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ Pen2011 | Serial | 1721 | ||
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| Author | Simone Balocco; Carlo Gatta; Francesco Ciompi; Oriol Pujol; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title | Combining Growcut and Temporal Correlation for IVUS Lumen Segmentation | Type | Conference Article | ||
| Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 6669 | Issue | Pages |
556-563 | |
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| Abstract | The assessment of arterial luminal area, performed by IVUS analysis, is a clinical index used to evaluate the degree of coronary artery disease. In this paper we propose a novel approach to automatically segment the vessel lumen, which combines model-based temporal information extracted from successive frames of the sequence, with spatial classification using the Growcut algorithm. The performance of the method is evaluated by an in vivo experiment on 300 IVUS frames. The automatic and manual segmentation performances in general vessel and stent frames are comparable. The average segmentation error in vessel, stent and bifurcation frames are 0.17±0.08 mm, 0.18±0.07 mm and 0.31±0.12 mm respectively. | ||||
| Address | Las Palmas de Gran Canaria. Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Berlin | Editor | Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-21256-7 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ BGC2011a | Serial | 1741 | ||
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| Author | Xavier Perez Sala; Cecilio Angulo; Sergio Escalera | ||||
| Title | Biologically Inspired Path Execution Using SURF Flow in Robot Navigation | Type | Conference Article | ||
| Year | 2011 | Publication | 11th International Work Conference on Artificial Neural Networks | Abbreviated Journal | |
| Volume | II | Issue | Pages |
581--588 | |
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| Abstract | An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo. | ||||
| Address | Malaga | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-21497-4 | Medium | |
| Area | Expedition | Conference | IWANN | ||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ PAE2011b | Serial | 1773 | ||
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| Author | Anjan Dutta; Josep Llados; Umapada Pal | ||||
| Title | A Bag-of-Paths Based Serialized Subgraph Matching for Symbol Spotting in Line Drawings | Type | Conference Article | ||
| Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 6669 | Issue | Pages |
620-627 | |
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| Abstract | In this paper we propose an error tolerant subgraph matching algorithm based on bag-of-paths for solving the problem of symbol spotting in line drawings. Bag-of-paths is a factorized representation of graphs where the factorization is done by considering all the acyclic paths between each pair of connected nodes. Similar paths within the whole collection of documents are clustered and organized in a lookup table for efficient indexing. The lookup table contains the index key of each cluster and the corresponding list of locations as a single entry. The mean path of each of the clusters serves as the index key for each table entry. The spotting method is then formulated by a spatial voting scheme to the list of locations of the paths that are decided in terms of search of similar paths that compose the query symbol. Efficient indexing of common substructures helps to reduce the computational burden of usual graph based methods. The proposed method can also be seen as a way to serialize graphs which allows to reduce the complexity of the subgraph isomorphism. We have encoded the paths in terms of both attributed strings and turning functions, and presented a comparative results between them within the symbol spotting framework. Experimentations for matching different shape silhouettes are also reported and the method has been proved to work in noisy environment also. | ||||
| Address | Las Palmas de Gran Canaria. Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Berlin | Editor | Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-21256-7 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ DLP2011a | Serial | 1738 | ||
| Permanent link to this record | |||||
| Author | Arnau Ramisa; Alex Goldhoorn; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras | ||||
| Title | Combining Invariant Features and the ALV Homing Method for Autonomous Robot Navigation Based on Panoramas | Type | Journal Article | ||
| Year | 2011 | Publication | Journal of Intelligent and Robotic Systems | Abbreviated Journal | JIRC |
| Volume | 64 | Issue | 3-4 | Pages |
625-649 |
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| Abstract | Biologically inspired homing methods, such as the Average Landmark Vector, are an interesting solution for local navigation due to its simplicity. However, usually they require a modification of the environment by placing artificial landmarks in order to work reliably. In this paper we combine the Average Landmark Vector with invariant feature points automatically detected in panoramic images to overcome this limitation. The proposed approach has been evaluated first in simulation and, as promising results are found, also in two data sets of panoramas from real world environments. | ||||
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| Publisher | Springer Netherlands | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0921-0296 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | RV;ADAS | Approved | no | ||
| Call Number | Admin @ si @ RGA2011 | Serial | 1728 | ||
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| Author | David Fernandez; Josep Llados; Alicia Fornes | ||||
| Title | Handwritten Word Spotting in Old Manuscript Images Using a Pseudo-Structural Descriptor Organized in a Hash Structure | Type | Conference Article | ||
| Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 6669 | Issue | Pages |
628-635 | |
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| Abstract | There are lots of historical handwritten documents with information that can be used for several studies and projects. The Document Image Analysis and Recognition community is interested in preserving these documents and extracting all the valuable information from them. Handwritten word-spotting is the pattern classification task which consists in detecting handwriting word images. In this work, we have used a query-by-example formalism: we have matched an input image with one or multiple images from handwritten documents to determine the distance that might indicate a correspondence. We have developed an approach based in characteristic Loci Features stored in a hash structure. Document images of the marriage licences of the Cathedral of Barcelona are used as the benchmarking database. | ||||
| Address | Las Palmas de Gran Canaria. Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | Jordi Vitria; Joao Miguel Raposo; Mario Hernandez | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-642-21256-7 | Medium | ||
| Area | Expedition | Conference | IbPRIA | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ FLF2011 | Serial | 1742 | ||
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| Author | Gemma Roig; Xavier Boix; F. de la Torre; Joan Serrat; C. Vilella | ||||
| Title | Hierarchical CRF with product label spaces for parts-based Models | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE Conference on Automatic Face and Gesture Recognition | Abbreviated Journal | |
| Volume | Issue | Pages |
657-664 | ||
| Keywords | Shape; Computational modeling; Principal component analysis; Random variables; Color; Upper bound; Facial features | ||||
| Abstract | Non-rigid object detection is a challenging an open research problem in computer vision. It is a critical part in many applications such as image search, surveillance, human-computer interaction or image auto-annotation. Most successful approaches to non-rigid object detection make use of part-based models. In particular, Conditional Random Fields (CRF) have been successfully embedded into a discriminative parts-based model framework due to its effectiveness for learning and inference (usually based on a tree structure). However, CRF-based approaches do not incorporate global constraints and only model pairwise interactions. This is especially important when modeling object classes that may have complex parts interactions (e.g. facial features or body articulations), because neglecting them yields an oversimplified model with suboptimal performance. To overcome this limitation, this paper proposes a novel hierarchical CRF (HCRF). The main contribution is to build a hierarchy of part combinations by extending the label set to a hierarchy of product label spaces. In order to keep the inference computation tractable, we propose an effective method to reduce the new label set. We test our method on two applications: facial feature detection on the Multi-PIE database and human pose estimation on the Buffy dataset. | ||||
| Address | Santa Barbara, CA, USA, 2011 | ||||
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| Area | Expedition | Conference | FG | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ RBT2011 | Serial | 1862 | ||
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