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	Author	Andreas Møgelmose; Chris Bahnsen; Thomas B. Moeslund; Albert Clapes; Sergio Escalera
	Title	Tri-modal Person Re-identification with RGB, Depth and Thermal Features			Type	Conference Article
	Year	2013	Publication	9th IEEE Workshop on Perception beyond the visible Spectrum, Computer Vision and Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	301-307
	Keywords
	Abstract	Person re-identification is about recognizing people who have passed by a sensor earlier. Previous work is mainly based on RGB data, but in this work we for the first time present a system where we combine RGB, depth, and thermal data for re-identification purposes. First, from each of the three modalities, we obtain some particular features: from RGB data, we model color information from different regions of the body, from depth data, we compute different soft body biometrics, and from thermal data, we extract local structural information. Then, the three information types are combined in a joined classifier. The tri-modal system is evaluated on a new RGB-D-T dataset, showing successful results in re-identification scenarios.
	Address	Portland; oregon; June 2013
	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	978-0-7695-4990-3	Medium
	Area		Expedition		Conference	CVPRW
	Notes	HUPBA;MILAB			Approved	no
	Call Number	Admin @ si @ MBM2013			Serial	2253
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	Author	Pau Baiget; Xavier Roca; Jordi Gonzalez
	Title	Autonomous Virtual Agents for Performance Evaluation of Tracking Algorithms			Type	Book Chapter
	Year	2008	Publication	Articulated Motion and Deformable Objects, 5th International Conference AMDO 2008,	Abbreviated Journal
	Volume	5098	Issue		Pages	299-308
	Keywords
	Abstract
	Address	Port d'Andratx (Mallorca)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	ISE @ ise @ BRG2008			Serial	974
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	Author	Agata Lapedriza; Santiago Segui; David Masip; Jordi Vitria
	Title	A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning			Type	Journal
	Year	2008	Publication	Pattern Analysis and Applications, Special Issue: Non–Parametric Distance–Based Classification Techniques and Their Applications,	Abbreviated Journal
	Volume	11	Issue	3-4	Pages	299-308
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	Springer	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 @ LSM2008			Serial	996
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	Author	Fadi Dornaika; Angel Sappa
	Title	Real Time Image Registration for Planar Structure and 3D Sensor Pose Estimation			Type	Book Chapter
	Year	2008	Publication	Stereo Vision	Abbreviated Journal
	Volume	18	Issue		Pages	299–316
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor	Asim Bhatti
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ DoS2008c			Serial	1057
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	Author	Miguel Oliveira; Angel Sappa; V. Santos
	Title	Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models			Type	Conference Article
	Year	2012	Publication	IEEE Intelligent Vehicles Symposium	Abbreviated Journal
	Volume		Issue		Pages	299-303
	Keywords
	Abstract	The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.
	Address	Alcalá de Henares
	Corporate Author				Thesis
	Publisher	IEEE Xplore	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1931-0587	ISBN	978-1-4673-2119-8	Medium
	Area		Expedition		Conference	IV
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ OSS2012b			Serial	2021
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	Author	Joan Serrat; Felipe Lumbreras; Antonio Lopez
	Title	Cost estimation of custom hoses from STL files and CAD drawings			Type	Journal Article
	Year	2013	Publication	Computers in Industry	Abbreviated Journal	COMPUTIND
	Volume	64	Issue	3	Pages	299-309
	Keywords	On-line quotation; STL format; Regression; Gaussian process
	Abstract	We present a method for the cost estimation of custom hoses from CAD models. They can come in two formats, which are easy to generate: a STL file or the image of a CAD drawing showing several orthogonal projections. The challenges in either cases are, first, to obtain from them a high level 3D description of the shape, and second, to learn a regression function for the prediction of the manufacturing time, based on geometric features of the reconstructed shape. The chosen description is the 3D line along the medial axis of the tube and the diameter of the circular sections along it. In order to extract it from STL files, we have adapted RANSAC, a robust parametric fitting algorithm. As for CAD drawing images, we propose a new technique for 3D reconstruction from data entered on any number of orthogonal projections. The regression function is a Gaussian process, which does not constrain the function to adopt any specific form and is governed by just two parameters. We assess the accuracy of the manufacturing time estimation by k-fold cross validation on 171 STL file models for which the time is provided by an expert. The results show the feasibility of the method, whereby the relative error for 80% of the testing samples is below 15%.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier	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	ADAS; 600.057; 600.054; 605.203			Approved	no
	Call Number	Admin @ si @ SLL2013; ADAS @ adas @			Serial	2161
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	Author	Maria Salamo; Sergio Escalera; Petia Radeva
	Title	Quality Enhancement based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender			Type	Conference Article
	Year	2009	Publication	8th International Conference on Case-Based Reasoning	Abbreviated Journal
	Volume	5650	Issue		Pages	298–312
	Keywords
	Abstract	Personalizing the product recommendation task is a major focus of research in the area of conversational recommender systems. Conversational case-based recommender systems help users to navigate through product spaces, alternatively making product suggestions and eliciting users feedback. Critiquing is a common form of feedback and incremental critiquing-based recommender system has shown its efficiency to personalize products based primarily on a quality measure. This quality measure influences the recommendation process and it is obtained by the combination of compatibility and similarity scores. In this paper, we describe new compatibility strategies whose basis is on reinforcement learning and a new feature weighting technique which is based on the user’s history of critiques. Moreover, we show that our methodology can significantly improve recommendation efficiency in comparison with the state-of-the-art approaches.
	Address	Seattle, USA
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-02998-1	Medium
	Area		Expedition		Conference	ICCBR
	Notes	HuPBA; MILAB			Approved	no
	Call Number	BCNPCL @ bcnpcl @ SER2009			Serial	1187
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	Author	Khalid El Asnaoui; Petia Radeva
	Title	Automatically Assess Day Similarity Using Visual Lifelogs			Type	Journal Article
	Year	2020	Publication	International Journal of Intelligent Systems	Abbreviated Journal	IJIS
	Volume	29	Issue		Pages	298–310
	Keywords
	Abstract	Today, we witness the appearance of many lifelogging cameras that are able to capture the life of a person wearing the camera and which produce a large number of images everyday. Automatically characterizing the experience and extracting patterns of behavior of individuals from this huge collection of unlabeled and unstructured egocentric data present major challenges and require novel and efficient algorithmic solutions. The main goal of this work is to propose a new method to automatically assess day similarity from the lifelogging images of a person. We propose a technique to measure the similarity between images based on the Swain’s distance and generalize it to detect the similarity between daily visual data. To this purpose, we apply the dynamic time warping (DTW) combined with the Swain’s distance for final day similarity estimation. For validation, we apply our technique on the Egocentric Dataset of University of Barcelona (EDUB) of 4912 daily images acquired by four persons with preliminary encouraging results.
	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; no proj			Approved	no
	Call Number	AsR2020			Serial	3409
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	Author	O. Fors; A. Richichi; Xavier Otazu; J. Nuñez
	Title	A new wavelet-based approach for the automated treatment of large sets of lunar occultation data			Type	Journal
	Year	2008	Publication	Astronomy and Astrohysics	Abbreviated Journal
	Volume	480	Issue		Pages	297–304
	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	CIC			Approved	no
	Call Number	CAT @ cat @ FRO2008			Serial	934
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	Author	Partha Pratim Roy; Umapada Pal; Josep Llados
	Title	Recognition of Multi-oriented Touching Characters in Graphical Documents			Type	Conference Article
	Year	2008	Publication	Computer Vision, Graphics & Image Processing, 2008. Sixth Indian Conference on,	Abbreviated Journal
	Volume	16	Issue		Pages	297–304
	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	ICVGIP ’08
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ RPL2008c			Serial	1080
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	Author	Marc Oliu; Ciprian Corneanu; Kamal Nasrollahi; Olegs Nikisins; Sergio Escalera; Yunlian Sun; Haiqing Li; Zhenan Sun; Thomas B. Moeslund; Modris Greitans
	Title	Improved RGB-D-T based Face Recognition			Type	Journal Article
	Year	2016	Publication	IET Biometrics	Abbreviated Journal	BIO
	Volume	5	Issue	4	Pages	297 - 303
	Keywords
	Abstract	Reliable facial recognition systems are of crucial importance in various applications from entertainment to security. Thanks to the deep-learning concepts introduced in the field, a significant improvement in the performance of the unimodal facial recognition systems has been observed in the recent years. At the same time a multimodal facial recognition is a promising approach. This study combines the latest successes in both directions by applying deep learning convolutional neural networks (CNN) to the multimodal RGB, depth, and thermal (RGB-D-T) based facial recognition problem outperforming previously published results. Furthermore, a late fusion of the CNN-based recognition block with various hand-crafted features (local binary patterns, histograms of oriented gradients, Haar-like rectangular features, histograms of Gabor ordinal measures) is introduced, demonstrating even better recognition performance on a benchmark RGB-D-T database. The obtained results in this study show that the classical engineered features and CNN-based features can complement each other for recognition purposes.
	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;MILAB;			Approved	no
	Call Number	Admin @ si @ OCN2016			Serial	2854
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	Author	Muhammad Anwer Rao; Fahad Shahbaz Khan; Joost Van de Weijer; Jorma Laaksonen
	Title	Top-Down Deep Appearance Attention for Action Recognition			Type	Conference Article
	Year	2017	Publication	20th Scandinavian Conference on Image Analysis	Abbreviated Journal
	Volume	10269	Issue		Pages	297-309
	Keywords	Action recognition; CNNs; Feature fusion
	Abstract	Recognizing human actions in videos is a challenging problem in computer vision. Recently, convolutional neural network based deep features have shown promising results for action recognition. In this paper, we investigate the problem of fusing deep appearance and motion cues for action recognition. We propose a video representation which combines deep appearance and motion based local convolutional features within the bag-of-deep-features framework. Firstly, dense deep appearance and motion based local convolutional features are extracted from spatial (RGB) and temporal (flow) networks, respectively. Both visual cues are processed in parallel by constructing separate visual vocabularies for appearance and motion. A category-specific appearance map is then learned to modulate the weights of the deep motion features. The proposed representation is discriminative and binds the deep local convolutional features to their spatial locations. Experiments are performed on two challenging datasets: JHMDB dataset with 21 action classes and ACT dataset with 43 categories. The results clearly demonstrate that our approach outperforms both standard approaches of early and late feature fusion. Further, our approach is only employing action labels and without exploiting body part information, but achieves competitive performance compared to the state-of-the-art deep features based approaches.
	Address	Tromso; June 2017
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	SCIA
	Notes	LAMP; 600.109; 600.068; 600.120			Approved	no
	Call Number	Admin @ si @ RKW2017b			Serial	3039
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	Author	Antonio Clavelli; Dimosthenis Karatzas; Josep Llados; Mario Ferraro; Giuseppe Boccignone
	Title	Towards Modelling an Attention-Based Text Localization Process			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	296-303
	Keywords	text localization; visual attention; eye guidance
	Abstract	This note introduces a visual attention model of text localization in real-world scenes. The core of the model built upon the proto-object concept is discussed. It is shown how such dynamic mid-level representation of the scene can be derived in the framework of an action-perception loop engaging salience, text information value computation, and eye guidance mechanisms. Preliminary results that compare model generated scanpaths with those eye-tracked from human subjects are presented.
	Address	Madeira; Portugal; June 2013
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-38627-5	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ CKL2013			Serial	2291
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	Author	Simeon Petkov; Xavier Carrillo; Petia Radeva; Carlo Gatta
	Title	Diaphragm border detection in coronary X-ray angiographies: New method and applications			Type	Journal Article
	Year	2014	Publication	Computerized Medical Imaging and Graphics	Abbreviated Journal	CMIG
	Volume	38	Issue	4	Pages	296-305
	Keywords
	Abstract	X-ray angiography is widely used in cardiac disease diagnosis during or prior to intravascular interventions. The diaphragm motion and the heart beating induce gray-level changes, which are one of the main obstacles in quantitative analysis of myocardial perfusion. In this paper we focus on detecting the diaphragm border in both single images or whole X-ray angiography sequences. We show that the proposed method outperforms state of the art approaches. We extend a previous publicly available data set, adding new ground truth data. We also compose another set of more challenging images, thus having two separate data sets of increasing difficulty. Finally, we show three applications of our method: (1) a strategy to reduce false positives in vessel enhanced images; (2) a digital diaphragm removal algorithm; (3) an improvement in Myocardial Blush Grade semi-automatic estimation.
	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; LAMP; 600.079			Approved	no
	Call Number	Admin @ si @ PCR2014			Serial	2468
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	Author	Laura Igual; Santiago Segui; Jordi Vitria; Fernando Azpiroz; Petia Radeva
	Title	Eigenmotion-Based Detection of Intestinal Contractions			Type	Conference Article
	Year	2007	Publication	Computer Analysis of Images and Patterns, 12th International Conference	Abbreviated Journal
	Volume	4673	Issue		Pages	293–300
	Keywords
	Abstract
	Address	Vienna (Austria)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-540-74271-5	Medium
	Area		Expedition		Conference	CAIP
	Notes	OR;MILAB;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ ISV2007a			Serial	895
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