Publicacions CVC -- Query Results

	Publicacions CVC Home \| Show All \| Simple Search \| Advanced Search \| Add Record \| Import	Login Quick Search: Field: contains: ...
	1–15 of 52 records found matching your query (RSS \| history):

Search & Display Options

Select All Deselect All

<< 1 2 3 4 >>

List View

Citations

Details

	Records
	Author	Xim Cerda-Company; C. Alejandro Parraga; Xavier Otazu
	Title	Which tone-mapping is the best? A comparative study of tone-mapping perceived quality			Type	Abstract
	Year	2014	Publication	Perception	Abbreviated Journal
	Volume	43	Issue		Pages	106
	Keywords
	Abstract	Perception 43 ECVP Abstract Supplement High-dynamic-range (HDR) imaging refers to the methods designed to increase the brightness dynamic range present in standard digital imaging techniques. This increase is achieved by taking the same picture under dierent exposure values and mapping the intensity levels into a single image by way of a tone-mapping operator (TMO). Currently, there is no agreement on how to evaluate the quality of dierent TMOs. In this work we psychophysically evaluate 15 dierent TMOs obtaining rankings based on the perceived properties of the resulting tone-mapped images. We performed two dierent experiments on a CRT calibrated display using 10 subjects: (1) a study of the internal relationships between grey-levels and (2) a pairwise comparison of the resulting 15 tone-mapped images. In (1) observers internally matched the grey-levels to a reference inside the tone-mapped images and in the real scene. In (2) observers performed a pairwise comparison of the tone-mapped images alongside the real scene. We obtained two rankings of the TMOs according their performance. In (1) the best algorithm was ICAM by J.Kuang et al (2007) and in (2) the best algorithm was a TMO by Krawczyk et al (2005). Our results also show no correlation between these two rankings.
	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	ECVP
	Notes	NEUROBIT; 600.074			Approved	no
	Call Number	Admin @ si @ CPO2014			Serial	2527
Permanent link to this record



	Author	Xavier Otazu; Olivier Penacchio; Xim Cerda-Company
	Title	Brightness and colour induction through contextual influences in V1			Type	Conference Article
	Year	2015	Publication	Scottish Vision Group 2015 SGV2015	Abbreviated Journal
	Volume	12	Issue	9	Pages	1208-2012
	Keywords
	Abstract
	Address	Carnoustie; Scotland; March 2015
	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	SGV
	Notes	NEUROBIT;			Approved	no
	Call Number	Admin @ si @ OPC2015a			Serial	2632
Permanent link to this record



	Author	Xavier Otazu; Olivier Penacchio; Xim Cerda-Company
	Title	An excitatory-inhibitory firing rate model accounts for brightness induction, colour induction and visual discomfort			Type	Conference Article
	Year	2015	Publication	Barcelona Computational, Cognitive and Systems Neuroscience	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Barcelona; June 2015
	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	BARCCSYN
	Notes	NEUROBIT;			Approved	no
	Call Number	Admin @ si @ OPC2015b			Serial	2634
Permanent link to this record



	Author	Stefan Ameling; Stephan Wirth; Dietrich Paulus; Gerard Lacey; Fernando Vilariño
	Title	Texture-based Polyp Detection in Colonoscopy			Type	Conference Article
	Year	2009	Publication	Proc. BILDVERARBEITUNG FÜR DIE MEDIZIN	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	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	800	Expedition		Conference
	Notes	MV;SIAI			Approved	no
	Call Number	fernando @ fernando @			Serial	2428
Permanent link to this record



	Author	Oscar Argudo; Marc Comino; Antonio Chica; Carlos Andujar; Felipe Lumbreras
	Title	Segmentation of aerial images for plausible detail synthesis			Type	Journal Article
	Year	2018	Publication	Computers & Graphics	Abbreviated Journal	CG
	Volume	71	Issue		Pages	23-34
	Keywords	Terrain editing; Detail synthesis; Vegetation synthesis; Terrain rendering; Image segmentation
	Abstract	The visual enrichment of digital terrain models with plausible synthetic detail requires the segmentation of aerial images into a suitable collection of categories. In this paper we present a complete pipeline for segmenting high-resolution aerial images into a user-defined set of categories distinguishing e.g. terrain, sand, snow, water, and different types of vegetation. This segmentation-for-synthesis problem implies that per-pixel categories must be established according to the algorithms chosen for rendering the synthetic detail. This precludes the definition of a universal set of labels and hinders the construction of large training sets. Since artists might choose to add new categories on the fly, the whole pipeline must be robust against unbalanced datasets, and fast on both training and inference. Under these constraints, we analyze the contribution of common per-pixel descriptors, and compare the performance of state-of-the-art supervised learning algorithms. We report the findings of two user studies. The first one was conducted to analyze human accuracy when manually labeling aerial images. The second user study compares detailed terrains built using different segmentation strategies, including official land cover maps. These studies demonstrate that our approach can be used to turn digital elevation models into fully-featured, detailed terrains with minimal authoring efforts.
	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	0097-8493	ISBN		Medium
	Area		Expedition		Conference
	Notes	MSIAU; 600.086; 600.118			Approved	no
	Call Number	Admin @ si @ ACC2018			Serial	3147
Permanent link to this record



	Author	Olivier Penacchio; Xavier Otazu; A. wilkins; J. Harris
	Title	Uncomfortable images prevent lateral interactions in the cortex from providing a sparse code			Type	Conference Article
	Year	2015	Publication	European Conference on Visual Perception ECVP2015	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Liverpool; uk; August 2015
	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	ECVP
	Notes	NEUROBIT;			Approved	no
	Call Number	Admin @ si @ POW2015			Serial	2633
Permanent link to this record



	Author	Mohammad N. S. Jahromi; Pau Buch Cardona; Egils Avots; Kamal Nasrollahi; Sergio Escalera; Thomas B. Moeslund; Gholamreza Anbarjafari
	Title	Privacy-Constrained Biometric System for Non-cooperative Users			Type	Journal Article
	Year	2019	Publication	Entropy	Abbreviated Journal	ENTROPY
	Volume	21	Issue	11	Pages	1033
	Keywords	biometric recognition; multimodal-based human identification; privacy; deep learning
	Abstract	With the consolidation of the new data protection regulation paradigm for each individual within the European Union (EU), major biometric technologies are now confronted with many concerns related to user privacy in biometric deployments. When individual biometrics are disclosed, the sensitive information about his/her personal data such as financial or health are at high risk of being misused or compromised. This issue can be escalated considerably over scenarios of non-cooperative users, such as elderly people residing in care homes, with their inability to interact conveniently and securely with the biometric system. The primary goal of this study is to design a novel database to investigate the problem of automatic people recognition under privacy constraints. To do so, the collected data-set contains the subject’s hand and foot traits and excludes the face biometrics of individuals in order to protect their privacy. We carried out extensive simulations using different baseline methods, including deep learning. Simulation results show that, with the spatial features extracted from the subject sequence in both individual hand or foot videos, state-of-the-art deep models provide promising recognition performance.
	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	HuPBA; no proj			Approved	no
	Call Number	Admin @ si @ NBA2019			Serial	3313
Permanent link to this record



	Author	Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; I. Bardaji; Horst Bunke
	Title	A Generic Framework for Median Graph Computation based on a Recursive Embedding Approach			Type	Journal Article
	Year	2011	Publication	Computer Vision and Image Understanding	Abbreviated Journal	CVIU
	Volume	115	Issue	7	Pages	919-928
	Keywords	Median Graph, Graph Embedding, Graph Matching, Structural Pattern Recognition
	Abstract	The median graph has been shown to be a good choice to obtain a represen- tative of a set of graphs. However, its computation is a complex problem. Recently, graph embedding into vector spaces has been proposed to obtain approximations of the median graph. The problem with such an approach is how to go from a point in the vector space back to a graph in the graph space. The main contribution of this paper is the generalization of this previ- ous method, proposing a generic recursive procedure that permits to recover the graph corresponding to a point in the vector space, introducing only the amount of approximation inherent to the use of graph matching algorithms. In order to evaluate the proposed method, we compare it with the set me- dian and with the other state-of-the-art embedding-based methods for the median graph computation. The experiments are carried out using four dif- ferent databases (one semi-artificial and three containing real-world data). Results show that with the proposed approach we can obtain better medi- ans, in terms of the sum of distances to the training graphs, than with the previous existing methods.
	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			Approved	no
	Call Number	IAM @ iam @ FKV2011			Serial	1831
Permanent link to this record



	Author	Maria Vanrell; Jordi Vitria; Xavier Roca
	Title	A multidimensional scaling approach to explore the behavior of a texture perception algorithm.			Type	Journal Article
	Year	1997	Publication	Machine Vision and Applications	Abbreviated Journal
	Volume	9	Issue		Pages	262–271
	Keywords
	Abstract
	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	OR;ISE;CIC;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VVR1997			Serial	35
Permanent link to this record



	Author	Maria Salamo; Sergio Escalera
	Title	Increasing Retrieval Quality in Conversational Recommenders			Type	Journal Article
	Year	2011	Publication	IEEE Transactions on Knowledge and Data Engineering	Abbreviated Journal	TKDE
	Volume	99	Issue		Pages	1-1
	Keywords
	Abstract	IF JCR CCIA 2.286 2009 24/103 JCR Impact Factor 2010: 1.851 A major task of research in conversational recommender systems is personalization. Critiquing is a common and powerful form of feedback, where a user can express her feature preferences by applying a series of directional critiques over the recommendations instead of providing speciﬁc preference values. Incremental Critiquing is a conversational recommender system that uses critiquing as a feedback to efﬁciently personalize products. The expectation is that in each cycle the system retrieves the products that best satisfy the user’s soft product preferences from a minimal information input. In this paper, we present a novel technique that increases retrieval quality based on a combination of compatibility and similarity scores. Under the hypothesis that a user learns Turing the recommendation process, we propose two novel exponential reinforcement learning approaches for compatibility that take into account both the instant at which the user makes a critique and the number of satisﬁed critiques. Moreover, we consider that the impact of features on the similarity differs according to the preferences manifested by the user. We propose a global weighting approach that uses a common weight for nearest cases in order to focus on groups of relevant products. We show that our methodology signiﬁcantly improves recommendation efﬁciency in four data sets of different sizes in terms of session length in comparison with state-of-the-art approaches. Moreover, our recommender shows higher robustness against noisy user data when compared to classical approaches
	Address
	Corporate Author				Thesis
	Publisher	IEEE	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1041-4347	ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB; HuPBA			Approved	no
	Call Number	Admin @ si @ SaE2011			Serial	1713
Permanent link to this record



	Author	Maria Elena Meza-de-Luna; Juan Ramon Terven Salinas; Bogdan Raducanu; Joaquin Salas
	Title	Assessing the Influence of Mirroring on the Perception of Professional Competence using Wearable Technology			Type	Journal Article
	Year	2016	Publication	IEEE Transactions on Affective Computing	Abbreviated Journal	TAC
	Volume	9	Issue	2	Pages	161-175
	Keywords	Mirroring; Nodding; Competence; Perception; Wearable Technology
	Abstract	Nonverbal communication is an intrinsic part in daily face-to-face meetings. A frequently observed behavior during social interactions is mirroring, in which one person tends to mimic the attitude of the counterpart. This paper shows that a computer vision system could be used to predict the perception of competence in dyadic interactions through the automatic detection of mirroring events. To prove our hypothesis, we developed: (1) A social assistant for mirroring detection, using a wearable device which includes a video camera and (2) an automatic classifier for the perception of competence, using the number of nodding gestures and mirroring events as predictors. For our study, we used a mixed-method approach in an experimental design where 48 participants acting as customers interacted with a confederated psychologist. We found that the number of nods or mirroring events has a significant influence on the perception of competence. Our results suggest that: (1) Customer mirroring is a better predictor than psychologist mirroring; (2) the number of psychologist’s nods is a better predictor than the number of customer’s nods; (3) except for the psychologist mirroring, the computer vision algorithm we used worked about equally well whether it was acquiring images from wearable smartglasses or fixed cameras.
	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	LAMP; 600.072;			Approved	no
	Call Number	Admin @ si @ MTR2016			Serial	2826
Permanent link to this record



	Author	Manuel Graña; Bogdan Raducanu
	Title	Special Issue on Bioinspired and knowledge based techniques and applications			Type	Journal Article
	Year	2015	Publication	Neurocomputing	Abbreviated Journal	NEUCOM
	Volume		Issue		Pages	1-3
	Keywords
	Abstract
	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	LAMP;			Approved	no
	Call Number	Admin @ si @ GrR2015			Serial	2598
Permanent link to this record



	Author	Manuel Carbonell; Alicia Fornes; Mauricio Villegas; Josep Llados
	Title	A Neural Model for Text Localization, Transcription and Named Entity Recognition in Full Pages			Type	Journal Article
	Year	2020	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	136	Issue		Pages	219-227
	Keywords
	Abstract	In the last years, the consolidation of deep neural network architectures for information extraction in document images has brought big improvements in the performance of each of the tasks involved in this process, consisting of text localization, transcription, and named entity recognition. However, this process is traditionally performed with separate methods for each task. In this work we propose an end-to-end model that combines a one stage object detection network with branches for the recognition of text and named entities respectively in a way that shared features can be learned simultaneously from the training error of each of the tasks. By doing so the model jointly performs handwritten text detection, transcription, and named entity recognition at page level with a single feed forward step. We exhaustively evaluate our approach on different datasets, discussing its advantages and limitations compared to sequential approaches. The results show that the model is capable of benefiting from shared features by simultaneously solving interdependent tasks.
	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; 600.140; 601.311; 600.121			Approved	no
	Call Number	Admin @ si @ CFV2020			Serial	3451
Permanent link to this record



	Author	M. Bressan; Jordi Vitria
	Title	Independent Component Analysis and Naïve Bayes Classification.			Type	Conference Article
	Year	2002	Publication	Proceedings of the Second IASTED International Conference Visualilzation, Imaging and Image Proceesing VIIP 2002: 496–501.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	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	OR;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ BrV2002a			Serial	288
Permanent link to this record



	Author	Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu
	Title	New Opportunities for Computer Vision-Based Assistive Technology Systems for the Visually Impaired			Type	Journal Article
	Year	2014	Publication	Computer	Abbreviated Journal	COMP
	Volume	47	Issue	4	Pages	52-58
	Keywords
	Abstract	Computing advances and increased smartphone use gives technology system designers greater flexibility in exploiting computer vision to support visually impaired users. Understanding these users' needs will certainly provide insight for the development of improved usability of computing devices.
	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	0018-9162	ISBN		Medium
	Area		Expedition		Conference
	Notes	LAMP;			Approved	no
	Call Number	Admin @ si @ TSR2014a			Serial	2317
Permanent link to this record