Publicacions CVC -- Query Results

	Publicacions CVC Home \| Show All \| Simple Search \| Advanced Search \| Add Record \| Import	Login Quick Search: Field: contains: ...
	1996–2010 of 3413 records found matching your query (RSS):

Search & Display Options

Select All Deselect All

[121–130] << 131 132 133 134 135 136 137 138 139 140 >> [141–150]

List View

Citations

Details

	Records
	Author	M. Visani; Oriol Ramos Terrades; Salvatore Tabbone
	Title	A Protocol to Characterize the Descriptive Power and the Complementarity of Shape Descriptors			Type	Journal Article
	Year	2011	Publication	International Journal on Document Analysis and Recognition	Abbreviated Journal	IJDAR
	Volume	14	Issue	1	Pages	87-100
	Keywords	Document analysis; Shape descriptors; Symbol description; Performance characterization; Complementarity analysis
	Abstract	Most document analysis applications rely on the extraction of shape descriptors, which may be grouped into different categories, each category having its own advantages and drawbacks (O.R. Terrades et al. in Proceedings of ICDAR’07, pp. 227–231, 2007). In order to improve the richness of their description, many authors choose to combine multiple descriptors. Yet, most of the authors who propose a new descriptor content themselves with comparing its performance to the performance of a set of single state-of-the-art descriptors in a specific applicative context (e.g. symbol recognition, symbol spotting...). This results in a proliferation of the shape descriptors proposed in the literature. In this article, we propose an innovative protocol, the originality of which is to be as independent of the final application as possible and which relies on new quantitative and qualitative measures. We introduce two types of measures: while the measures of the first type are intended to characterize the descriptive power (in terms of uniqueness, distinctiveness and robustness towards noise) of a descriptor, the second type of measures characterizes the complementarity between multiple descriptors. Characterizing upstream the complementarity of shape descriptors is an alternative to the usual approach where the descriptors to be combined are selected by trial and error, considering the performance characteristics of the overall system. To illustrate the contribution of this protocol, we performed experimental studies using a set of descriptors and a set of symbols which are widely used by the community namely ART and SC descriptors and the GREC 2003 database.
	Address
	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
	Notes	DAG; IF 1.091			Approved	no
	Call Number	Admin @ si @VRT2011			Serial	1856
Permanent link to this record



	Author	Carles Sanchez
	Title	Tracheal ring detection in bronchoscopy			Type	Report
	Year	2011	Publication	CVC Technical Report	Abbreviated Journal
	Volume	168	Issue		Pages
	Keywords	Bronchoscopy, tracheal ring, segmentation
	Abstract	Endoscopy is the process in which a camera is introduced inside a human. Given that endoscopy provides realistic images (in contrast to other modalities) and allows non-invase minimal intervention procedures (which can aid in diagnosis and surgical interventions), its use has spreaded during last decades. In this project we will focus on bronchoscopic procedures, during which the camera is introduced through the trachea in order to have a diagnostic of the patient. The diagnostic interventions are focused on: degree of stenosis (reduction in tracheal area), prosthesis or early diagnosis of tumors. In the first case, assessment of the luminal area and the calculation of the diameters of the tracheal rings are required. A main limitation is that all the process is done by hand, which means that the doctor takes all the measurements and decisions just by looking at the screen. As far as we know there is no computational framework for helping the doctors in the diagnosis. This project will consist of analysing bronchoscopic videos in order to extract useful information for the diagnostic of the degree of stenosis. In particular we will focus on segmentation of the tracheal rings. As a result of this project several strategies (for detecting tracheal rings) had been implemented in order to compare their performance.
	Address
	Corporate Author				Thesis	Master's thesis
	Publisher		Place of Publication		Editor	Debora Gil, F.Javier Sanchez
	Language	english	Summary Language	english	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	IAM;MV			Approved	no
	Call Number	IAM @ iam @ San2011			Serial	1841
Permanent link to this record



	Author	Hamdi Dibeklioglu; M.O. Hortas; I. Kosunen; P. Zuzánek; Albert Ali Salah; Theo Gevers
	Title	Design and implementation of an affect-responsive interactive photo frame			Type	Journal
	Year	2011	Publication	Journal on Multimodal User Interfaces	Abbreviated Journal	JMUI
	Volume	4	Issue	2	Pages	81-95
	Keywords
	Abstract	This paper describes an affect-responsive interactive photo-frame application that offers its user a different experience with every use. It relies on visual analysis of activity levels and facial expressions of its users to select responses from a database of short video segments. This ever-growing database is automatically prepared by an offline analysis of user-uploaded videos. The resulting system matches its user’s affect along dimensions of valence and arousal, and gradually adapts its response to each specific user. In an extended mode, two such systems are coupled and feed each other with visual content. The strengths and weaknesses of the system are assessed through a usability study, where a Wizard-of-Oz response logic is contrasted with the fully automatic system that uses affective and activity-based features, either alone, or in tandem.
	Address
	Corporate Author				Thesis
	Publisher	Springer–Verlag	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1783-7677	ISBN		Medium
	Area		Expedition		Conference
	Notes	ALTRES;ISE			Approved	no
	Call Number	Admin @ si @ DHK2011			Serial	1842
Permanent link to this record



	Author	A. Toet; M. Henselmans; M.P. Lucassen; Theo Gevers
	Title	Emotional effects of dynamic textures			Type	Journal
	Year	2011	Publication	i-Perception	Abbreviated Journal	iPER
	Volume	2	Issue	9	Pages	969 – 991
	Keywords
	Abstract	This study explores the effects of various spatiotemporal dynamic texture characteristics on human emotions. The emotional experience of auditory (eg, music) and haptic repetitive patterns has been studied extensively. In contrast, the emotional experience of visual dynamic textures is still largely unknown, despite their natural ubiquity and increasing use in digital media. Participants watched a set of dynamic textures, representing either water or various different media, and self-reported their emotional experience. Motion complexity was found to have mildly relaxing and nondominant effects. In contrast, motion change complexity was found to be arousing and dominant. The speed of dynamics had arousing, dominant, and unpleasant effects. The amplitude of dynamics was also regarded as unpleasant. The regularity of the dynamics over the textures’ area was found to be uninteresting, nondominant, mildly relaxing, and mildly pleasant. The spatial scale of the dynamics had an unpleasant, arousing, and dominant effect, which was larger for textures with diverse content than for water textures. For water textures, the effects of spatial contrast were arousing, dominant, interesting, and mildly unpleasant. None of these effects were observed for textures of diverse content. The current findings are relevant for the design and synthesis of affective multimedia content and for affective scene indexing and retrieval.
	Address
	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	2041-6695	ISBN		Medium
	Area		Expedition		Conference
	Notes	ALTRES;ISE			Approved	no
	Call Number	Admin @ si @THL2011			Serial	1843
Permanent link to this record



	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
	Address
	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
	Notes	ALTRES;ISE			Approved	no
	Call Number	Admin @ si @ LGG2011			Serial	1844
Permanent link to this record



	Author	G.D. Evangelidis; Ferran Diego; Joan Serrat; Antonio Lopez
	Title	Slice Matching for Accurate Spatio-Temporal Alignment			Type	Conference Article
	Year	2011	Publication	In ICCV Workshop on Visual Surveillance	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	video alignment
	Abstract	Video synchronization and alignment is a rather recent topic in computer vision. It usually deals with the problem of aligning sequences recorded simultaneously by static, jointly- or independently-moving cameras. In this paper, we investigate the more difficult problem of matching videos captured at different times from independently-moving cameras, whose trajectories are approximately coincident or parallel. To this end, we propose a novel method that pixel-wise aligns videos and allows thus to automatically highlight their differences. This primarily aims at visual surveillance but the method can be adopted as is by other related video applications, like object transfer (augmented reality) or high dynamic range video. We build upon a slice matching scheme to first synchronize the sequences, while we develop a spatio-temporal alignment scheme to spatially register corresponding frames and refine the temporal mapping. We investigate the performance of the proposed method on videos recorded from vehicles driven along different types of roads and compare with related previous works.
	Address
	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	VS
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ EDS2011; ADAS @ adas @ eds2011a			Serial	1861
Permanent link to this record



	Author	G. 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
	Keywords
	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
	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	FG
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ RBT2011			Serial	1862
Permanent link to this record



	Author	Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell
	Title	Portmanteau Vocabularies for Multi-Cue Image Representation			Type	Conference Article
	Year	2011	Publication	25th Annual Conference on Neural Information Processing Systems	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	We describe a novel technique for feature combination in the bag-of-words model of image classification. Our approach builds discriminative compound words from primitive cues learned independently from training images. Our main observation is that modeling joint-cue distributions independently is more statistically robust for typical classification problems than attempting to empirically estimate the dependent, joint-cue distribution directly. We use Information theoretic vocabulary compression to find discriminative combinations of cues and the resulting vocabulary of portmanteau words is compact, has the cue binding property, and supports individual weighting of cues in the final image representation. State-of-the-art results on both the Oxford Flower-102 and Caltech-UCSD Bird-200 datasets demonstrate the effectiveness of our technique compared to other, significantly more complex approaches to multi-cue image representation
	Address
	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	NIPS
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ KWB2011			Serial	1865
Permanent link to this record



	Author	Naila Murray; Sandra Skaff; Luca Marchesotti; Florent Perronnin
	Title	Towards Automatic Concept Transfer			Type	Conference Article
	Year	2011	Publication	Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Non-Photorealistic Animation and Rendering	Abbreviated Journal
	Volume		Issue		Pages	167.176
	Keywords	chromatic modeling, color concepts, color transfer, concept transfer
	Abstract	This paper introduces a novel approach to automatic concept transfer; examples of concepts are “romantic”, “earthy”, and “luscious”. The approach modifies the color content of an input image given only a concept specified by a user in natural language, thereby requiring minimal user input. This approach is particularly useful for users who are aware of the message they wish to convey in the transferred image while being unsure of the color combination needed to achieve the corresponding transfer. The user may adjust the intensity level of the concept transfer to his/her liking with a single parameter. The proposed approach uses a convex clustering algorithm, with a novel pruning mechanism, to automatically set the complexity of models of chromatic content. It also uses the Earth-Mover's Distance to compute a mapping between the models of the input image and the target chromatic concept. Results show that our approach yields transferred images which effectively represent concepts, as confirmed by a user study.
	Address
	Corporate Author				Thesis
	Publisher	ACM Press	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4503-0907-3	Medium
	Area		Expedition		Conference	NPAR
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ MSM2011			Serial	1866
Permanent link to this record



	Author	Jordi Roca; C. Alejandro Parraga; Maria Vanrell
	Title	Categorical Focal Colours are Structurally Invariant Under Illuminant Changes			Type	Conference Article
	Year	2011	Publication	European Conference on Visual Perception	Abbreviated Journal
	Volume		Issue		Pages	196
	Keywords
	Abstract	The visual system perceives the colour of surfaces approximately constant under changes of illumination. In this work, we investigate how stable is the perception of categorical \“focal\” colours and their interrelations with varying illuminants and simple chromatic backgrounds. It has been proposed that best examples of colour categories across languages cluster in small regions of the colour space and are restricted to a set of 11 basic terms (Kay and Regier, 2003 Proceedings of the National Academy of Sciences of the USA 100 9085\–9089). Following this, we developed a psychophysical paradigm that exploits the ability of subjects to reliably reproduce the most representative examples of each category, adjusting multiple test patches embedded in a coloured Mondrian. The experiment was run on a CRT monitor (inside a dark room) under various simulated illuminants. We modelled the recorded data for each subject and adapted state as a 3D interconnected structure (graph) in Lab space. The graph nodes were the subject\’s focal colours at each adaptation state. The model allowed us to get a better distance measure between focal structures under different illuminants. We found that perceptual focal structures tend to be preserved better than the structures of the physical \“ideal\” colours under illuminant changes.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title	Perception 40	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ECVP
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ RPV2011			Serial	1867
Permanent link to this record



	Author	Sergio Escalera; Ana Puig; Oscar Amoros; Maria Salamo
	Title	Intelligent GPGPU Classification in Volume Visualization: a framework based on Error-Correcting Output Codes			Type	Journal Article
	Year	2011	Publication	Computer Graphics Forum	Abbreviated Journal	CGF
	Volume	30	Issue	7	Pages	2107-2115
	Keywords
	Abstract	IF JCR 1.455 2010 25/99 In volume visualization, the definition of the regions of interest is inherently an iterative trial-and-error process finding out the best parameters to classify and render the final image. Generally, the user requires a lot of expertise to analyze and edit these parameters through multi-dimensional transfer functions. In this paper, we present a framework of intelligent methods to label on-demand multiple regions of interest. These methods can be split into a two-level GPU-based labelling algorithm that computes in time of rendering a set of labelled structures using the Machine Learning Error-Correcting Output Codes (ECOC) framework. In a pre-processing step, ECOC trains a set of Adaboost binary classifiers from a reduced pre-labelled data set. Then, at the testing stage, each classifier is independently applied on the features of a set of unlabelled samples and combined to perform multi-class labelling. We also propose an alternative representation of these classifiers that allows to highly parallelize the testing stage. To exploit that parallelism we implemented the testing stage in GPU-OpenCL. The empirical results on different data sets for several volume structures shows high computational performance and classification accuracy.
	Address
	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
	Notes	MILAB; HuPBA			Approved	no
	Call Number	Admin @ si @ EPA2011			Serial	1881
Permanent link to this record



	Author	Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Xavier Jimenez ; Oscar Vilarroya; Petia Radeva
	Title	A fully-automatic caudate nucleus segmentation of brain MRI: Application in volumetric analysis of pediatric attention-deficit/hyperactivity disorder			Type	Journal Article
	Year	2011	Publication	BioMedical Engineering Online	Abbreviated Journal	BEO
	Volume	10	Issue	105	Pages	1-23
	Keywords	Brain caudate nucleus; segmentation; MRI; atlas-based strategy; Graph Cut framework
	Abstract	Background Accurate automatic segmentation of the caudate nucleus in magnetic resonance images (MRI) of the brain is of great interest in the analysis of developmental disorders. Segmentation methods based on a single atlas or on multiple atlases have been shown to suitably localize caudate structure. However, the atlas prior information may not represent the structure of interest correctly. It may therefore be useful to introduce a more flexible technique for accurate segmentations. Method We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure. Results We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis. Conclusion CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD.
	Address
	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	1475-925X	ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ ISH2011			Serial	1882
Permanent link to this record



	Author	Mario Rojas; David Masip; A. Todorov; Jordi Vitria
	Title	Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models			Type	Journal Article
	Year	2011	Publication	PloS one	Abbreviated Journal	Plos
	Volume	6	Issue	8	Pages	e23323
	Keywords
	Abstract	JCR Impact Factor 2010: 4.411 Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions
	Address
	Corporate Author				Thesis
	Publisher	Public Library of Science	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
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ RMT2011			Serial	1883
Permanent link to this record



	Author	Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva
	Title	On the Design of Low Redundancy Error-Correcting Output Codes			Type	Book Chapter
	Year	2011	Publication	Ensembles in Machine Learning Applications	Abbreviated Journal
	Volume	373	Issue	2	Pages	21-38
	Keywords
	Abstract	The classification of large number of object categories is a challenging trend in the Pattern Recognition field. In the literature, this is often addressed using an ensemble of classifiers . In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for combining classifiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a compact design of ECOC in terms of the number of classifiers. Evolutionary computation is used for tuning the parameters of the classifiers and looking for the best compact ECOC code configuration. The results over several public UCI data sets and different multi-class Computer Vision problems show that the proposed methodology obtains comparable (even better) results than the state-of-the-art ECOC methodologies with far less number of dichotomizers.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1860-949X	ISBN	978-3-642-22909-1	Medium
	Area		Expedition		Conference
	Notes	MILAB; OR;HuPBA;MV			Approved	no
	Call Number	Admin @ si @ BEB2011b			Serial	1886
Permanent link to this record



	Author	Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera
	Title	Introducing the Separability Matrix for Error Correcting Output Codes Coding			Type	Conference Article
	Year	2011	Publication	10th International Conference on Multiple Classifier Systems	Abbreviated Journal
	Volume	6713	Issue		Pages	227-236
	Keywords
	Abstract	Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results.
	Address	Napoles, Italy
	Corporate Author				Thesis
	Publisher	Springer-Verlag Berlin, Heidelberg	Place of Publication		Editor	Carlo Sansone; Josef Kittler; Fabio Roli
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-21556-8	Medium
	Area		Expedition		Conference	MCS
	Notes	MILAB; OR;HuPBA;MV			Approved	no
	Call Number	Admin @ si @ BPB2011b			Serial	1887
Permanent link to this record