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	Author	Agata Lapedriza; David Masip; Jordi Vitria
	Title	Face Verification using External Features			Type	Miscellaneous
	Year	2006	Publication	7th International Conference on Automatic Face and Gesture Recognition (FG´06), 132– 137	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Southampton (United Kingdom)
	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 @ LMV2006a			Serial	707
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	Author	Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados
	Title	Vers une approche foue of encapsulation de graphes: application a la reconnaissance de symboles			Type	Conference Article
	Year	2010	Publication	Colloque International Francophone sur l'Écrit et le Document	Abbreviated Journal
	Volume		Issue		Pages	169-184
	Keywords	Fuzzy interval; Graph embedding; Bayesian network; Symbol recognition
	Abstract	We present a new methodology for symbol recognition, by employing a structural approach for representing visual associations in symbols and a statistical classifier for recognition. A graphic symbol is vectorized, its topological and geometrical details are encoded by an attributed relational graph and a signature is computed for it. Data adapted fuzzy intervals have been introduced for addressing the sensitivity of structural representations to noise. The joint probability distribution of signatures is encoded by a Bayesian network, which serves as a mechanism for pruning irrelevant features and choosing a subset of interesting features from structural signatures of underlying symbol set, and is deployed in a supervised learning scenario for recognizing query symbols. Experimental results on pre-segmented 2D linear architectural and electronic symbols from GREC databases are presented.
	Address	Sousse, Tunisia
	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	CIFED
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ LBR2010a			Serial	1293
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	Author	Herve Locteau; Sebastien Mace; Ernest Valveny; Salvatore Tabbone
	Title	Extraction des pieces de un plan de habitation			Type	Conference Article
	Year	2010	Publication	Colloque Internacional Francophone de l´Ecrit et le Document	Abbreviated Journal
	Volume		Issue		Pages	1–12
	Keywords
	Abstract	In this article, a method to extract the rooms of an architectural floor plan image is described. We first present a line detection algorithm to extract long lines in the image. Those lines are analyzed to identify the existing walls. From this point, room extraction can be seen as a classical segmentation task for which each region corresponds to a room. The chosen resolution strategy consists in recursively decomposing the image until getting nearly convex regions. The notion of convexity is difficult to quantify, and the selection of separation lines can also be rough. Thus, we take advantage of knowledge associated to architectural floor plans in order to obtain mainly rectangular rooms. Preliminary tests on a set of real documents show promising results.
	Address	Sousse, Tunisia
	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	CIFED
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ LMV2010			Serial	1440
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	Author	Laura Lopez-Fuentes; Alessandro Farasin; Harald Skinnemoen; Paolo Garza
	Title	Deep Learning models for passability detection of flooded roads			Type	Conference Article
	Year	2018	Publication	MediaEval 2018 Multimedia Benchmark Workshop	Abbreviated Journal
	Volume	2283	Issue		Pages
	Keywords
	Abstract	In this paper we study and compare several approaches to detect floods and evidence for passability of roads by conventional means in Twitter. We focus on tweets containing both visual information (a picture shared by the user) and metadata, a combination of text and related extra information intrinsic to the Twitter API. This work has been done in the context of the MediaEval 2018 Multimedia Satellite Task.
	Address	Sophia Antipolis; France; October 2018
	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	MediaEval
	Notes	LAMP; 600.084; 600.109; 600.120			Approved	no
	Call Number	Admin @ si @ LFS2018			Serial	3224
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	Author	D. Rincon; E. Frumento; R. Fogliardi; M. Angel Viñas
	Title	Carmen/Carolin: Description and Results of an International Experience of Telemedicine.			Type	Miscellaneous
	Year	2000	Publication	ISTEP 2000 International Symposium on Telemedicine ang Teleeducation in Practice, 255–230.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Slovak Republic.
	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				Approved	no
	Call Number	ISE @ ise @ RFF2000			Serial	177
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	Author	Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika
	Title	Facial Expression Recognition based on Multi-view Observations with Application to Social Robotics			Type	Conference Article
	Year	2014	Publication	1st Workshop on Computer Vision for Affective Computing	Abbreviated Journal
	Volume		Issue		Pages	1-8
	Keywords
	Abstract	Human-robot interaction is a hot topic nowadays in the social robotics community. One crucial aspect is represented by the affective communication which comes encoded through the facial expressions. In this paper, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, view- and texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial expression.
	Address	Singapore; November 2014
	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	ACCV
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ RBD2014			Serial	2599
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	Author	Guillem Martinez; Maya Aghaei; Martin Dijkstra; Bhalaji Nagarajan; Femke Jaarsma; Jaap van de Loosdrecht; Petia Radeva; Klaas Dijkstra
	Title	Hyper-Spectral Imaging for Overlapping Plastic Flakes Segmentation			Type	Conference Article
	Year	2022	Publication	47th International Conference on Acoustics, Speech, and Signal Processing	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Hyper-spectral imaging; plastic sorting; multi-label segmentation; bitfield encoding
	Abstract	In this paper, we propose a deformable convolution-based generative adversarial network (DCNGAN) for perceptual quality enhancement of compressed videos. DCNGAN is also adaptive to the quantization parameters (QPs). Compared with optical flows, deformable convolutions are more effective and efficient to align frames. Deformable convolutions can operate on multiple frames, thus leveraging more temporal information, which is beneficial for enhancing the perceptual quality of compressed videos. Instead of aligning frames in a pairwise manner, the deformable convolution can process multiple frames simultaneously, which leads to lower computational complexity. Experimental results demonstrate that the proposed DCNGAN outperforms other state-of-the-art compressed video quality enhancement algorithms.
	Address	Singapore; May 2022
	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	ICASSP
	Notes	MILAB; no proj			Approved	no
	Call Number	Admin @ si @ MAD2022			Serial	3767
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	Author	Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis
	Title	3D Gait Estimation from Monoscopic Video			Type	Miscellaneous
	Year	2004	Publication	IEEE International Conference on Image Processing	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Singapore
	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	ADAS			Approved	no
	Call Number	ADAS @ adas @ SAM2004c			Serial	495
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	Author	Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan Carlos Moure
	Title	Embedded Real-time Stixel Computation			Type	Conference Article
	Year	2017	Publication	GPU Technology Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	GPU; CUDA; Stixels; Autonomous Driving
	Abstract
	Address	Silicon Valley; USA; May 2017
	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	GTC
	Notes	ADAS; 600.118			Approved	no
	Call Number	ADAS @ adas @ HEV2017a			Serial	2879
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	Author	Victor Campmany; Sergio Silva; Juan Carlos Moure; Toni Espinosa; David Vazquez; Antonio Lopez
	Title	GPU-based pedestrian detection for autonomous driving			Type	Conference Article
	Year	2016	Publication	GPU Technology Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Pedestrian Detection; GPU
	Abstract	Pedestrian detection for autonomous driving is one of the hardest tasks within computer vision, and involves huge computational costs. Obtaining acceptable real-time performance, measured in frames per second (fps), for the most advanced algorithms is nowadays a hard challenge. Taking the work in [1] as our baseline, we propose a CUDA implementation of a pedestrian detection system that includes LBP and HOG as feature descriptors and SVM and Random forest as classifiers. We introduce significant algorithmic adjustments and optimizations to adapt the problem to the NVIDIA GPU architecture. The aim is to deploy a real-time system providing reliable results.
	Address	Silicon Valley; San Francisco; USA; April 2016
	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	GTC
	Notes	ADAS; 600.085; 600.082; 600.076			Approved	no
	Call Number	ADAS @ adas @ CSM2016			Serial	2737
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	Author	Daniel Hernandez; Juan Carlos Moure; Toni Espinosa; Alejandro Chacon; David Vazquez; Antonio Lopez
	Title	Real-time 3D Reconstruction for Autonomous Driving via Semi-Global Matching			Type	Conference Article
	Year	2016	Publication	GPU Technology Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Stereo; Autonomous Driving; GPU; 3d reconstruction
	Abstract	Robust and dense computation of depth information from stereo-camera systems is a computationally demanding requirement for real-time autonomous driving. Semi-Global Matching (SGM) [1] approximates heavy-computation global algorithms results but with lower computational complexity, therefore it is a good candidate for a real-time implementation. SGM minimizes energy along several 1D paths across the image. The aim of this work is to provide a real-time system producing reliable results on energy-efficient hardware. Our design runs on a NVIDIA Titan X GPU at 104.62 FPS and on a NVIDIA Drive PX at 6.7 FPS, promising for real-time platforms
	Address	Silicon Valley; San Francisco; USA; April 2016
	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	GTC
	Notes	ADAS; 600.085; 600.082; 600.076			Approved	no
	Call Number	ADAS @ adas @ HME2016			Serial	2738
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	Author	Partha Pratim Roy; Umapada Pal; Josep Llados
	Title	Seal Object Detection in Document Images using GHT of Local Component Shapes			Type	Conference Article
	Year	2010	Publication	10th ACM Symposium On Applied Computing	Abbreviated Journal
	Volume		Issue		Pages	23–27
	Keywords
	Abstract	Due to noise, overlapped text/signature and multi-oriented nature, seal (stamp) object detection involves a difficult challenge. This paper deals with automatic detection of seal from documents with cluttered background. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors (distance and angular position) computed from recognition result of individual connected components (characters). Recognition of multi-scale and multi-oriented component is done using Support Vector Machine classifier. Generalized Hough Transform (GHT) is used to detect the seal and a voting is casted for finding possible location of the seal object in a document based on these spatial feature descriptor of components pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal object in a document. Experimental results show that, the method is efficient to locate seal instance of arbitrary shape and orientation in documents.
	Address	Sierre, Switzerland
	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	SAC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ RPL2010a			Serial	1291
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	Author	Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero
	Title	Recurrent Comparator with attention models to detect counterfeit documents			Type	Conference Article
	Year	2019	Publication	15th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	This paper is focused on the detection of counterfeit documents via the recurrent comparison of the security textured background regions of two images. The main contributions are twofold: first we apply and adapt a recurrent comparator architecture with attention mechanism to the counterfeit detection task, which constructs a representation of the background regions by recurrently condition the next observation, learning the difference between genuine and counterfeit images through iterative glimpses. Second we propose a new counterfeit document dataset to ensure the generalization of the learned model towards the detection of the lack of resolution during the counterfeit manufacturing. The presented network, outperforms state-of-the-art classification approaches for counterfeit detection as demonstrated in the evaluation.
	Address	Sidney; Australia; September 2019
	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	ICDAR
	Notes	DAG; 600.140; 600.121; 601.269			Approved	no
	Call Number	Admin @ si @ BRL2019			Serial	3456
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	Author	Sergio Escalera; Jordi Gonzalez; Xavier Baro; Miguel Reyes; Oscar Lopes; Isabelle Guyon; V. Athitsos; Hugo Jair Escalante
	Title	Multi-modal Gesture Recognition Challenge 2013: Dataset and Results			Type	Conference Article
	Year	2013	Publication	15th ACM International Conference on Multimodal Interaction	Abbreviated Journal
	Volume		Issue		Pages	445-452
	Keywords
	Abstract	The recognition of continuous natural gestures is a complex and challenging problem due to the multi-modal nature of involved visual cues (e.g. fingers and lips movements, subtle facial expressions, body pose, etc.), as well as technical limitations such as spatial and temporal resolution and unreliable depth cues. In order to promote the research advance on this field, we organized a challenge on multi-modal gesture recognition. We made available a large video database of 13; 858 gestures from a lexicon of 20 Italian gesture categories recorded with a KinectTM camera, providing the audio, skeletal model, user mask, RGB and depth images. The focus of the challenge was on user independent multiple gesture learning. There are no resting positions and the gestures are performed in continuous sequences lasting 1-2 minutes, containing between 8 and 20 gesture instances in each sequence. As a result, the dataset contains around 1:720:800 frames. In addition to the 20 main gesture categories, ‘distracter’ gestures are included, meaning that additional audio and gestures out of the vocabulary are included. The final evaluation of the challenge was defined in terms of the Levenshtein edit distance, where the goal was to indicate the real order of gestures within the sequence. 54 international teams participated in the challenge, and outstanding results were obtained by the first ranked participants.
	Address	Sidney; Australia; December 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	978-1-4503-2129-7	Medium
	Area		Expedition		Conference	ICMI
	Notes	HUPBA; ISE; 600.063;MV			Approved	no
	Call Number	Admin @ si @ EGB2013			Serial	2373
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	Author	Victor Ponce; Sergio Escalera; Xavier Baro
	Title	Multi-modal Social Signal Analysis for Predicting Agreement in Conversation Settings			Type	Conference Article
	Year	2013	Publication	15th ACM International Conference on Multimodal Interaction	Abbreviated Journal
	Volume		Issue		Pages	495-502
	Keywords
	Abstract	In this paper we present a non-invasive ambient intelligence framework for the analysis of non-verbal communication applied to conversational settings. In particular, we apply feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues coming from the fields of psychology and observational methodology. We test our methodology over data captured in victim-offender mediation scenarios. Using different state-of-the-art classification approaches, our system achieve upon 75% of recognition predicting agreement among the parts involved in the conversations, using as ground truth the experts opinions.
	Address	Sidney; Australia; December 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	978-1-4503-2129-7	Medium
	Area		Expedition		Conference	ICMI
	Notes	HuPBA;MV			Approved	no
	Call Number	Admin @ si @ PEB2013			Serial	2488
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