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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 | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| ISSN | 0302-9743 | ISBN | 978-3-642-21497-4 | Medium | |
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Expedition | Conference | IWANN | ||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ PAE2011b | Serial | 1773 | ||
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| Author | Oscar Amoros; Sergio Escalera; Anna Puig | ||||
| Title | Adaboost GPU-based Classifier for Direct Volume Rendering | Type | Conference Article | ||
| Year | 2011 | Publication | International Conference on Computer Graphics Theory and Applications | Abbreviated Journal | |
| Volume | Issue | Pages | 215-219 | ||
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| Abstract | In volume visualization, the voxel visibitity and materials are carried out through an interactive editing of Transfer Function. In this paper, we present a two-level GPU-based labeling method that computes in times of rendering a set of labeled structures using the Adaboost machine learning classifier. In a pre-processing step, Adaboost trains a binary classifier from a pre-labeled dataset and, in each sample, takes into account a set of features. This binary classifier is a weighted combination of weak classifiers, which can be expressed as simple decision functions estimated on a single feature values. Then, at the testing stage, each weak classifier is independently applied on the features of a set of unlabeled samples. We propose an alternative representation of these classifiers that allow a GPU-based parallelizated testing stage embedded into the visualization pipeline. The empirical results confirm the OpenCL-based classification of biomedical datasets as a tough problem where an opportunity for further research emerges. | ||||
| Address | Algarve, Portugal | ||||
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Expedition | Conference | GRAPP | ||
| Notes | MILAB; HuPBA | Approved | no | ||
| Call Number | Admin @ si @ AEP2011 | Serial | 1774 | ||
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| Author | Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva | ||||
| Title | Compact Evolutive Design of Error-Correcting Output Codes. Supervised and Unsupervised Ensemble Methods and Applications | Type | Conference Article | ||
| Year | 2010 | Publication | European Conference on Machine Learning | Abbreviated Journal | |
| Volume | I | Issue | Pages | 119-128 | |
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Expedition | Conference | ECML | ||
| Notes | MILAB; OR;HUPBA;MV | Approved | no | ||
| Call Number | Admin @ si @ BEB2010 | Serial | 1775 | ||
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| Author | Bhaskar Chakraborty; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez | ||||
| Title | Selective Spatio-Temporal Interest Points | Type | Journal Article | ||
| Year | 2012 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
| Volume | 116 | Issue | 3 | Pages | 396-410 |
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| Abstract | Recent progress in the field of human action recognition points towards the use of Spatio-TemporalInterestPoints (STIPs) for local descriptor-based recognition strategies. In this paper, we present a novel approach for robust and selective STIP detection, by applying surround suppression combined with local and temporal constraints. This new method is significantly different from existing STIP detection techniques and improves the performance by detecting more repeatable, stable and distinctive STIPs for human actors, while suppressing unwanted background STIPs. For action representation we use a bag-of-video words (BoV) model of local N-jet features to build a vocabulary of visual-words. To this end, we introduce a novel vocabulary building strategy by combining spatial pyramid and vocabulary compression techniques, resulting in improved performance and efficiency. Action class specific Support Vector Machine (SVM) classifiers are trained for categorization of human actions. A comprehensive set of experiments on popular benchmark datasets (KTH and Weizmann), more challenging datasets of complex scenes with background clutter and camera motion (CVC and CMU), movie and YouTube video clips (Hollywood 2 and YouTube), and complex scenes with multiple actors (MSR I and Multi-KTH), validates our approach and show state-of-the-art performance. Due to the unavailability of ground truth action annotation data for the Multi-KTH dataset, we introduce an actor specific spatio-temporal clustering of STIPs to address the problem of automatic action annotation of multiple simultaneous actors. Additionally, we perform cross-data action recognition by training on source datasets (KTH and Weizmann) and testing on completely different and more challenging target datasets (CVC, CMU, MSR I and Multi-KTH). This documents the robustness of our proposed approach in the realistic scenario, using separate training and test datasets, which in general has been a shortcoming in the performance evaluation of human action recognition techniques. | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1077-3142 | ISBN | Medium | ||
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Expedition | Conference | |||
| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ CHM2012 | Serial | 1806 | ||
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| Author | Noha Elfiky; Fahad Shahbaz Khan; Joost Van de Weijer; Jordi Gonzalez | ||||
| Title | Discriminative Compact Pyramids for Object and Scene Recognition | Type | Journal Article | ||
| Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 45 | Issue | 4 | Pages | 1627-1636 |
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| Abstract | Spatial pyramids have been successfully applied to incorporating spatial information into bag-of-words based image representation. However, a major drawback is that it leads to high dimensional image representations. In this paper, we present a novel framework for obtaining compact pyramid representation. First, we investigate the usage of the divisive information theoretic feature clustering (DITC) algorithm in creating a compact pyramid representation. In many cases this method allows us to reduce the size of a high dimensional pyramid representation up to an order of magnitude with little or no loss in accuracy. Furthermore, comparison to clustering based on agglomerative information bottleneck (AIB) shows that our method obtains superior results at significantly lower computational costs. Moreover, we investigate the optimal combination of multiple features in the context of our compact pyramid representation. Finally, experiments show that the method can obtain state-of-the-art results on several challenging data sets. | ||||
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| ISSN | 0031-3203 | ISBN | Medium | ||
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| Notes | ISE; CAT;CIC | Approved | no | ||
| Call Number | Admin @ si @ EKW2012 | Serial | 1807 | ||
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| Author | Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras | ||||
| Title | The IIIA30 MObile Robot Object Recognition Datset | Type | Conference Article | ||
| Year | 2011 | Publication | 11th Portuguese Robotics Open | Abbreviated Journal | |
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| Abstract | Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones. | ||||
| Address | Lisboa | ||||
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Expedition | Conference | Robotica | ||
| Notes | RV;ADAS | Approved | no | ||
| Call Number | Admin @ si @ RAV2011 | Serial | 1777 | ||
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| Author | Joost Van de Weijer; Shida Beigpour | ||||
| Title | The Dichromatic Reflection Model: Future Research Directions and Applications | Type | Conference Article | ||
| Year | 2011 | Publication | International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | dblp | ||||
| Abstract | The dichromatic reflection model (DRM) predicts that color distributions form a parallelogram in color space, whose shape is defined by the body reflectance and the illuminant color. In this paper we resume the assumptions which led to the DRM and shortly recall two of its main applications domains: color image segmentation and photometric invariant feature computation. After having introduced the model we discuss several limitations of the theory, especially those which are raised once working on real-world uncalibrated images. In addition, we summerize recent extensions of the model which allow to handle more complicated light interactions. Finally, we suggest some future research directions which would further extend its applicability. | ||||
| Address | Algarve, Portugal | ||||
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| Publisher | SciTePress | Place of Publication | Editor | Mestetskiy, Leonid and Braz, José | |
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| ISSN | ISBN | 978-989-8425-47-8 | Medium | ||
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Expedition | Conference | VISIGRAPP | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ WeB2011 | Serial | 1778 | ||
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| Author | Carolina Malagelada; F.De Lorio; Fernando Azpiroz; Santiago Segui; Petia Radeva; Anna Accarino; J.Santos; Juan R. Malagelada | ||||
| Title | Intestinal Dysmotility in Patients with Functional Intestinal Disorders Demonstrated by Computer Vision Analysis of Capsule Endoscopy Images | Type | Conference Article | ||
| Year | 2010 | Publication | 18th United European Gastroenterology Week | Abbreviated Journal | |
| Volume | 56 | Issue | 3 | Pages | A19-20 |
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| Address | Barcelona | ||||
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Expedition | Conference | UEGW | ||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ MLA2010 | Serial | 1779 | ||
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| Author | Koen E.A. van de Sande; Jasper Uilings; Theo Gevers; Arnold Smeulders | ||||
| Title | Segmentation as Selective Search for Object Recognition | Type | Conference Article | ||
| Year | 2011 | Publication | 13th IEEE International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 1879-1886 | ||
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| Abstract | For object recognition, the current state-of-the-art is based on exhaustive search. However, to enable the use of more expensive features and classifiers and thereby progress beyond the state-of-the-art, a selective search strategy is needed. Therefore, we adapt segmentation as a selective search by reconsidering segmentation: We propose to generate many approximate locations over few and precise object delineations because (1) an object whose location is never generated can not be recognised and (2) appearance and immediate nearby context are most effective for object recognition. Our method is class-independent and is shown to cover 96.7% of all objects in the Pascal VOC 2007 test set using only 1,536 locations per image. Our selective search enables the use of the more expensive bag-of-words method which we use to substantially improve the state-of-the-art by up to 8.5% for 8 out of 20 classes on the Pascal VOC 2010 detection challenge. | ||||
| Address | Barcelona | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1550-5499 | ISBN | 978-1-4577-1101-5 | Medium | |
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Expedition | Conference | ICCV | ||
| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ SUG2011 | Serial | 1780 | ||
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| Author | Shida Beigpour; Joost Van de Weijer | ||||
| Title | Object Recoloring Based on Intrinsic Image Estimation | Type | Conference Article | ||
| Year | 2011 | Publication | 13th IEEE International Conference in Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 327 - 334 | ||
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| Abstract | Object recoloring is one of the most popular photo-editing tasks. The problem of object recoloring is highly under-constrained, and existing recoloring methods limit their application to objects lit by a white illuminant. Application of these methods to real-world scenes lit by colored illuminants, multiple illuminants, or interreflections, results in unrealistic recoloring of objects. In this paper, we focus on the recoloring of single-colored objects presegmented from their background. The single-color constraint allows us to fit a more comprehensive physical model to the object. We demonstrate that this permits us to perform realistic recoloring of objects lit by non-white illuminants, and multiple illuminants. Moreover, the model allows for more realistic handling of illuminant alteration of the scene. Recoloring results captured by uncalibrated cameras demonstrate that the proposed framework obtains realistic recoloring for complex natural images. Furthermore we use the model to transfer color between objects and show that the results are more realistic than existing color transfer methods. | ||||
| Address | Barcelona | ||||
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| ISSN | 1550-5499 | ISBN | 978-1-4577-1101-5 | Medium | |
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Expedition | Conference | ICCV | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ BeW2011 | Serial | 1781 | ||
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| Author | Joan M. Nuñez | ||||
| Title | Computer vision techniques for characterization of finger joints in X-ray image | Type | Report | ||
| Year | 2011 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 165 | Issue | Pages | ||
| Keywords | Rheumatoid arthritis, X-ray, Sharp Van der Heijde, joint characterization, sclerosis detection, bone detection, edge, ridge | ||||
| Abstract | Rheumatoid arthritis (RA) is an autoimmune inflammatory type of arthritis which mainly affects hands on its first stages. Though it is a chronic disease and there is no cure for it, treatments require an accurate assessment of illness evolution. Such assessment is based on evaluation of hand X-ray images by using one of the several available semi-quantitative methods. This task requires highly trained medical personnel. That is why the automation of the assessment would allow professionals to save time and effort. Two stages are involved in this task. Firstly, the joint detection, afterwards, the joint characterization. Unlike the little existing previous work, this contribution clearly separates those two stages and sets the foundations of a modular assessment system focusing on the characterization stage. A hand joint dataset is created and an accurate data analysis is achieved in order to identify relevant features. Since the sclerosis and the lower bone were decided to be the most important features, different computer vision techniques were used in order to develop a detector system for both of them. Joint space width measures are provided and their correlation with Sharp-Van der Heijde is verified | ||||
| Address | Bellaterra (Barcelona) | ||||
| Corporate Author | Computer Vision Center | Thesis | Master's thesis | ||
| Publisher | Place of Publication | Editor | Dr. Fernando Vilariño and Dra. Debora Gil | ||
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| Notes | MV;IAM; | Approved | no | ||
| Call Number | IAM @ iam @ Nuñ2011 | Serial | 1795 | ||
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| Author | Mohammad Rouhani; Angel Sappa | ||||
| Title | Implicit B-Spline Fitting Using the 3L Algorithm | Type | Conference Article | ||
| Year | 2011 | Publication | 18th IEEE International Conference on Image Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 893-896 | ||
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| Address | Brussels, Belgium | ||||
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Expedition | Conference | ICIP | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ RoS2011a; ADAS @ adas @ | Serial | 1782 | ||
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| Author | Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera | ||||
| Title | Analisis de la Expresion Oral y Gestual en Proyectos Fin de Carrera Via un Sistema de Vision Artificial | Type | Miscellaneous | ||
| Year | 2011 | Publication | Revista electronica de la asociacion de enseñantes universitarios de la informatica AENUI | Abbreviated Journal | ReVision |
| Volume | 4 | Issue | 1 | Pages | 8-18 |
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| Abstract | La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación. | ||||
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| ISSN | 1989-1199 | ISBN | Medium | ||
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| Notes | MILAB;HuPBA;MV | Approved | no | ||
| Call Number | Admin @ si @ PGB2011c | Serial | 1783 | ||
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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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| ISSN | 1083-4419 | ISBN | Medium | ||
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| Notes | MILAB; DAG;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ EFP2011 | Serial | 1784 | ||
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| Author | Javier Vazquez | ||||
| Title | Colour Constancy in Natural Through Colour Naming and Sensor Sharpening | Type | Book Whole | ||
| Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Colour is derived from three physical properties: incident light, object reflectance and sensor sensitivities. Incident light varies under natural conditions; hence, recovering scene illuminant is an important issue in computational colour. One way to deal with this problem under calibrated conditions is by following three steps, 1) building a narrow-band sensor basis to accomplish the diagonal model, 2) building a feasible set of illuminants, and 3) defining criteria to select the best illuminant. In this work we focus on colour constancy for natural images by introducing perceptual criteria in the first and third stages.
To deal with the illuminant selection step, we hypothesise that basic colour categories can be used as anchor categories to recover the best illuminant. These colour names are related to the way that the human visual system has evolved to encode relevant natural colour statistics. Therefore the recovered image provides the best representation of the scene labelled with the basic colour terms. We demonstrate with several experiments how this selection criterion achieves current state-of-art results in computational colour constancy. In addition to this result, we psychophysically prove that usual angular error used in colour constancy does not correlate with human preferences, and we propose a new perceptual colour constancy evaluation. The implementation of this selection criterion strongly relies on the use of a diagonal model for illuminant change. Consequently, the second contribution focuses on building an appropriate narrow-band sensor basis to represent natural images. We propose to use the spectral sharpening technique to compute a unique narrow-band basis optimised to represent a large set of natural reflectances under natural illuminants and given in the basis of human cones. The proposed sensors allow predicting unique hues and the World colour Survey data independently of the illuminant by using a compact singularity function. Additionally, we studied different families of sharp sensors to minimise different perceptual measures. This study brought us to extend the spherical sampling procedure from 3D to 6D. Several research lines still remain open. One natural extension would be to measure the effects of using the computed sharp sensors on the category hypothesis, while another might be to insert spatial contextual information to improve category hypothesis. Finally, much work still needs to be done to explore how individual sensors can be adjusted to the colours in a scene. |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Maria Vanrell;Graham D. Finlayson | |
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ Vaz2011a | Serial | 1785 | ||
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