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	Author	Xavier Otazu; J. Nuñez
	Title	Algoritmo de Clasificacion no Supervisada Basado en Wavelets.			Type	Miscellaneous
	Year	2001	Publication	Teledeteccion, Medio Ambiente y Cambio Global, IX Congreso Nacional de Teledeteccion, 437–440.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Lleida
	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 @ ONu2001			Serial	147
Permanent link to this record



	Author	Enric Marti; Jaume Rocarias; Debora Gil; Marc Vivet; Carme Julia
	Title	Uso de recursos virtuales en Aprendizaje Basado en Proyectos. Una experiencia en la asignatura de Graficos por Computador			Type	Miscellaneous
	Year	2008	Publication	Octava Jornada sobre Aprendizaje Cooperativo	Abbreviated Journal
	Volume		Issue		Pages	79–88
	Keywords
	Abstract	En esta comunicación presentamos una experiencia en Aprendizaje Basado en Proyectos (Project Based Learning – PBL) realizada los últimos cuatro años (cursos del 2004-05 al 2007-08) en Gráficos por Computador 2, asignatura optativa de tercer curso de Ingeniería Informática, titulación impartida en la Escuela Técnica Superior de Ingeniería (ETSE) de la Universidad Autónoma de Barcelona (UAB). Fruto de la constante voluntad de mejora de la organización ABP de nuestra asignatura nos decidimos a utilizar una herramienta LMS (Learning Management System) basada en Moodle y adaptada por nosotros llamada Caronte para poder gestionar la documentación generada en ABP, y añadir una componente semipresencial a la asignatura. En primer lugar se presenta la organización de nuestra asignatura, basada proponer al alumno dos itinerarios para cursarla: el itinerario ABP y el itinerario basado en clases magistrales i examen que llamaremos TPPE (Teoría, Problemas, Prácticas, Examen). La dinámica ABP nos genera una cantidad importante de documentación entre los grupos y el profesor, aparte de el feedback que el profesor genera a los alumnos. En la segunda parte del artículo presentamos los espacios docentes electrónicos de ambos itinerarios, con los que trabajan los alumnos. Finalmente, mostramos los resultados obtenidos de alumnos matriculados y de encuestas de valoración realizados por los alumnos para finalmente exponer las conclusiones de estos cuatro años de experiencia en ABP y en el uso de recursos virtuales en ABP, así como plantear mejoras y temas de discusión sobre ABP.
	Address	Lleida
	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	978-84-691-4605-7	Medium
	Area		Expedition		Conference
	Notes	IAM;ADAS;			Approved	no
	Call Number	IAM @ iam @ MRG2008a			Serial	1101
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	Author	Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	Depth of Valleys Accumulation Algorithm for Object Detection			Type	Conference Article
	Year	2011	Publication	14th Congrès Català en Intel·ligencia Artificial	Abbreviated Journal
	Volume	1	Issue	1	Pages	71-80
	Keywords	Object Recognition, Object Region Identification, Image Analysis, Image Processing
	Abstract	This work aims at detecting in which regions the objects in the image are by using information about the intensity of valleys, which appear to surround ob- jects in images where the source of light is in the line of direction than the camera. We present our depth of valleys accumulation method, which consists of two stages: first, the definition of the depth of valleys image which combines the output of a ridges and valleys detector with the morphological gradient to measure how deep is a point inside a valley and second, an algorithm that denotes points of the image as interior to objects those which are inside complete or incomplete boundaries in the depth of valleys image. To evaluate the performance of our method we have tested it on several application domains. Our results on object region identification are promising, specially in the field of polyp detection in colonoscopy videos, and we also show its applicability in different areas.
	Address	Lleida
	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	978-1-60750-841-0	Medium
	Area	800	Expedition		Conference	CCIA
	Notes	MV;SIAI			Approved	no
	Call Number	IAM @ iam @ BSV2011b			Serial	1699
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	Author	Xavier Perez Sala; Cecilio Angulo; Sergio Escalera
	Title	Biologically Inspired Turn Control in Robot Navigation			Type	Conference Article
	Year	2011	Publication	14th Congrès Català en Intel·ligencia Artificial	Abbreviated Journal
	Volume		Issue		Pages	187-196
	Keywords
	Abstract	An exportable and robust system for turn control using only camera images is proposed for path execution in robot navigation. Robot motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames in the image sequence. This information is used to compute the instantaneous rotation angle. Finally, control loop is closed correcting robot displacements when it is requested for a turn command. The proposed system has been successfully tested on the four-legged Sony Aibo robot.
	Address	Lleida
	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	978-1-60750-841-0	Medium
	Area		Expedition		Conference	CCIA
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ PAE2011a			Serial	1753
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	Author	Miquel Ferrer; Robert Benavente; Ernest Valveny; J. Garcia; Agata Lapedriza; Gemma Sanchez
	Title	Aprendizaje Cooperativo Aplicado a la Docencia de las Asignaturas de Programacion en Ingenieria Informatica			Type	Miscellaneous
	Year	2008	Publication	Octava Jornada sobre Aprendizaje Cooperativo, 41–46	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Lleida (Spain).
	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;DAG;CIC;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ FBV2008			Serial	955
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	Author	David Roche; Debora Gil; Jesus Giraldo
	Title	An inference model for analyzing termination conditions of Evolutionary Algorithms			Type	Conference Article
	Year	2011	Publication	14th Congrès Català en Intel·ligencia Artificial	Abbreviated Journal
	Volume		Issue		Pages	216-225
	Keywords	Evolutionary Computation Convergence, Termination Conditions, Statistical Inference
	Abstract	In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used. We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution.
	Address	Lleida, Catalonia (Spain)
	Corporate Author	Associació Catalana Intel·ligència Artificial			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	978-1-60750-841-0	Medium
	Area		Expedition		Conference	CCIA
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ RGG2011a			Serial	1677
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	Author	Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva
	Title	ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences			Type	Conference Article
	Year	2009	Publication	12th International Conference on Medical Image and Computer Assisted Intervention	Abbreviated Journal
	Volume	5762	Issue	II	Pages
	Keywords
	Abstract	The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from Intravascular ultrasound sequences. The segmentation is tackled as a classification problem where the contextual information is exploited by means of Conditional Random Fields (CRFs). A multi-class classification framework is proposed, and inference is achieved by combining binary CRFs according to the Error-Correcting-Output-Code technique. The results are validated against manually segmented sequences. Finally, the method is compared with other state-of-the-art classifiers.
	Address	London, UK
	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	978-3-642-04270-6	Medium
	Area		Expedition		Conference	MICCAI
	Notes	MILAB;HuPBA			Approved	no
	Call Number	BCNPCL @ bcnpcl @ CPF2009			Serial	1228
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	Author	Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez
	Title	Video alignment for automotive applications			Type	Miscellaneous
	Year	2009	Publication	BMVA one–day technical meeting on vision for automotive applications	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	video alignment
	Abstract
	Address	London, UK
	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 @ DPS2009			Serial	1271
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	Author	Jose Manuel Alvarez; Antonio Lopez
	Title	Model-based road detection using shadowless features and on-line learning			Type	Miscellaneous
	Year	2009	Publication	BMVA one–day technical meeting on vision for automotive applications	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	road detection
	Abstract
	Address	London, UK
	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 @ AlA2009			Serial	1272
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	Author	Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
	Title	Symbol recognition: current advances and perspectives			Type	Book Chapter
	Year	2002	Publication	Graphics Recognition Algorithms And Applications	Abbreviated Journal	LNCS
	Volume	2390	Issue		Pages	104-128
	Keywords
	Abstract	The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
	Address	London, UK
	Corporate Author				Thesis
	Publisher	Springer-Verlag	Place of Publication		Editor	Dorothea Blostein and Young- Bin Kwon
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	3-540-44066-6	Medium
	Area		Expedition		Conference	GREC
	Notes	DAG; IAM;			Approved	no
	Call Number	IAM @ iam @ LVS2002			Serial	1572
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	Author	Wenjuan Gong; Jürgen Brauer; Michael Arens; Jordi Gonzalez
	Title	Modeling vs. Learning Approaches for Monocular 3D Human Pose Estimation			Type	Conference Article
	Year	2011	Publication	1st IEEE International Workshop on Performance Evaluation on Recognition of Human Actions and Pose Estimation Methods	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	London, 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	PERHAPS
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ GBA2011			Serial	1812
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	Author	Arash Akbarinia; Raquel Gil Rodriguez; C. Alejandro Parraga
	Title	Colour Constancy: Biologically-inspired Contrast Variant Pooling Mechanism			Type	Conference Article
	Year	2017	Publication	28th British Machine Vision Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Pooling is a ubiquitous operation in image processing algorithms that allows for higher-level processes to collect relevant low-level features from a region of interest. Currently, max-pooling is one of the most commonly used operators in the computational literature. However, it can lack robustness to outliers due to the fact that it relies merely on the peak of a function. Pooling mechanisms are also present in the primate visual cortex where neurons of higher cortical areas pool signals from lower ones. The receptive fields of these neurons have been shown to vary according to the contrast by aggregating signals over a larger region in the presence of low contrast stimuli. We hypothesise that this contrast-variant-pooling mechanism can address some of the shortcomings of maxpooling. We modelled this contrast variation through a histogram clipping in which the percentage of pooled signal is inversely proportional to the local contrast of an image. We tested our hypothesis by applying it to the phenomenon of colour constancy where a number of popular algorithms utilise a max-pooling step (e.g. White-Patch, Grey-Edge and Double-Opponency). For each of these methods, we investigated the consequences of replacing their original max-pooling by the proposed contrast-variant-pooling. Our experiments on three colour constancy benchmark datasets suggest that previous results can significantly improve by adopting a contrast-variant-pooling mechanism.
	Address	London; September 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	BMVC
	Notes	NEUROBIT; 600.068; 600.072			Approved	no
	Call Number	Admin @ si @ AGP2017			Serial	2992
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	Author	Rada Deeb; Damien Muselet; Mathieu Hebert; Alain Tremeau; Joost Van de Weijer
	Title	3D color charts for camera spectral sensitivity estimation			Type	Conference Article
	Year	2017	Publication	28th British Machine Vision Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Estimating spectral data such as camera sensor responses or illuminant spectral power distribution from raw RGB camera outputs is crucial in many computer vision applications. Usually, 2D color charts with various patches of known spectral reflectance are used as reference for such purpose. Deducing n-D spectral data (n»3) from 3D RGB inputs is an ill-posed problem that requires a high number of inputs. Unfortunately, most of the natural color surfaces have spectral reflectances that are well described by low-dimensional linear models, i.e. each spectral reflectance can be approximated by a weighted sum of the others. It has been shown that adding patches to color charts does not help in practice, because the information they add is redundant with the information provided by the first set of patches. In this paper, we propose to use spectral data of higher dimensionality by using 3D color charts that create inter-reflections between the surfaces. These inter-reflections produce multiplications between natural spectral curves and so provide non-linear spectral curves. We show that such data provide enough information for accurate spectral data estimation.
	Address	London; September 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	BMVC
	Notes	LAMP; 600.109; 600.120			Approved	no
	Call Number	Admin @ si @ DMH2017b			Serial	3037
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	Author	Kai Wang; Fei Yang; Joost Van de Weijer
	Title	Attention Distillation: self-supervised vision transformer students need more guidance			Type	Conference Article
	Year	2022	Publication	33rd British Machine Vision Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Self-supervised learning has been widely applied to train high-quality vision transformers. Unleashing their excellent performance on memory and compute constraint devices is therefore an important research topic. However, how to distill knowledge from one self-supervised ViT to another has not yet been explored. Moreover, the existing self-supervised knowledge distillation (SSKD) methods focus on ConvNet based architectures are suboptimal for ViT knowledge distillation. In this paper, we study knowledge distillation of self-supervised vision transformers (ViT-SSKD). We show that directly distilling information from the crucial attention mechanism from teacher to student can significantly narrow the performance gap between both. In experiments on ImageNet-Subset and ImageNet-1K, we show that our method AttnDistill outperforms existing self-supervised knowledge distillation (SSKD) methods and achieves state-of-the-art k-NN accuracy compared with self-supervised learning (SSL) methods learning from scratch (with the ViT-S model). We are also the first to apply the tiny ViT-T model on self-supervised learning. Moreover, AttnDistill is independent of self-supervised learning algorithms, it can be adapted to ViT based SSL methods to improve the performance in future research.
	Address	London; UK; November 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	BMVC
	Notes	LAMP; 600.147			Approved	no
	Call Number	Admin @ si @ WYW2022			Serial	3793
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	Author	Kai Wang; Chenshen Wu; Andrew Bagdanov; Xialei Liu; Shiqi Yang; Shangling Jui; Joost Van de Weijer
	Title	Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification			Type	Conference Article
	Year	2022	Publication	33rd British Machine Vision Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Lifelong object re-identification incrementally learns from a stream of re-identification tasks. The objective is to learn a representation that can be applied to all tasks and that generalizes to previously unseen re-identification tasks. The main challenge is that at inference time the representation must generalize to previously unseen identities. To address this problem, we apply continual meta metric learning to lifelong object re-identification. To prevent forgetting of previous tasks, we use knowledge distillation and explore the roles of positive and negative pairs. Based on our observation that the distillation and metric losses are antagonistic, we propose to remove positive pairs from distillation to robustify model updates. Our method, called Distillation without Positive Pairs (DwoPP), is evaluated on extensive intra-domain experiments on person and vehicle re-identification datasets, as well as inter-domain experiments on the LReID benchmark. Our experiments demonstrate that DwoPP significantly outperforms the state-of-the-art.
	Address	London; UK; November 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	BMVC
	Notes	LAMP; 600.147			Approved	no
	Call Number	Admin @ si @ WWB2022			Serial	3794
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