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	Author	Jaume Gibert; Ernest Valveny; Horst Bunke
	Title	Dimensionality Reduction for Graph of Words Embedding			Type	Conference Article
	Year	2011	Publication	8th IAPR-TC-15 International Workshop. Graph-Based Representations in Pattern Recognition	Abbreviated Journal
	Volume	6658	Issue		Pages	22-31
	Keywords
	Abstract	The Graph of Words Embedding consists in mapping every graph of a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. While it shows good properties in classification problems, it suffers from high dimensionality and sparsity. These two issues are addressed in this article. Two well-known techniques for dimensionality reduction, kernel principal component analysis (kPCA) and independent component analysis (ICA), are applied to the embedded graphs. We discuss their performance compared to the classification of the original vectors on three different public databases of graphs.
	Address	Münster, Germany
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor	Xiaoyi Jiang; Miquel Ferrer; Andrea Torsello
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-20843-0	Medium
	Area		Expedition		Conference	GbRPR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ GVB2011a			Serial	1743
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	Author	Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich
	Title	Perception Based Representations for Computational Colour			Type	Conference Article
	Year	2011	Publication	3rd International Workshop on Computational Color Imaging	Abbreviated Journal
	Volume	6626	Issue		Pages	16-30
	Keywords	colour perception, induction, naming, psychophysical data, saliency, segmentation
	Abstract	The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space.
	Address	Milan, Italy
	Corporate Author				Thesis
	Publisher	Springer-Verlag	Place of Publication		Editor	Raimondo Schettini, Shoji Tominaga, Alain Trémeau
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-20403-6	Medium
	Area		Expedition		Conference	CCIW
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ VMB2011			Serial	1733
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	Author	Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados
	Title	Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval			Type	Conference Article
	Year	2011	Publication	33rd European Conference on Information Retrieval	Abbreviated Journal
	Volume	6611	Issue		Pages	314-325
	Keywords
	Abstract	In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset.
	Address	Dublin, Ireland
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication	Berlin	Editor	P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-20160-8	Medium
	Area		Expedition		Conference	ECIR
	Notes	DAG; RV;ADAS			Approved	no
	Call Number	Admin @ si @ RAK2011			Serial	1737
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	Author	Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin
	Title	Multi-Class Classification in Image Analysis Via Error-Correcting Output Codes			Type	Book Chapter
	Year	2011	Publication	Innovations in Intelligent Image Analysis	Abbreviated Journal
	Volume	339	Issue		Pages	7-29
	Keywords
	Abstract	A common way to model multi-class classification problems is by means of Error-Correcting Output Codes (ECOC). Given a multi-class problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem.A classification decision is obtained by assigning the label of the class with the closest code. In this paper, we overview the state-of-the-art on ECOC designs and test them in real applications. Results on different multi-class data sets show the benefits of using the ensemble of classifiers when categorizing objects in images.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication	Berlin	Editor	H. Kawasnicka; L.Jain
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1860-949X	ISBN	978-3-642-17933-4	Medium
	Area		Expedition		Conference
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ ETP2011			Serial	1746
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	Author	Fadi Dornaika; Bogdan Raducanu
	Title	Subtle Facial Expression Recognition in Still Images and Videos			Type	Book Chapter
	Year	2011	Publication	Advances in Face Image Analysis: Techniques and Technologies	Abbreviated Journal
	Volume		Issue	14	Pages	259-277
	Keywords
	Abstract	This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM).
	Address
	Corporate Author				Thesis
	Publisher	IGI-Global	Place of Publication	New York, USA	Editor	Yu-Jin Zhang
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-6152-0991-0	Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ DoR2011			Serial	1751
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	Author	Jaime Moreno; Xavier Otazu
	Title	Image compression algorithm based on Hilbert scanning of embedded quadTrees: an introduction of the Hi-SET coder			Type	Conference Article
	Year	2011	Publication	IEEE International Conference on Multimedia and Expo	Abbreviated Journal
	Volume		Issue		Pages	1-6
	Keywords
	Abstract	In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. The implementation of the proposed coder is developed for gray-scale and color image compression. Hi-SET compressed images are, on average, 6.20dB better than the ones obtained by other compression techniques based on the Hilbert scanning. Moreover, Hi-SET improves the image quality in 1.39dB and 1.00dB in gray-scale and color compression, respectively, when compared with JPEG2000 coder.
	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	1945-7871	ISBN	978-1-61284-348-3	Medium
	Area		Expedition		Conference	ICME
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ MoO2011a			Serial	2176
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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	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	Victor Ponce; Mario Gorga; Xavier Baro; Sergio Escalera
	Title	Human Behavior Analysis from Video Data Using Bag-of-Gestures			Type	Conference Article
	Year	2011	Publication	22nd International Joint Conference on Artificial Intelligence	Abbreviated Journal
	Volume	3	Issue		Pages	2836-2837
	Keywords
	Abstract	Human Behavior Analysis in Uncontrolled Environments can be categorized in two main challenges: 1) Feature extraction and 2) Behavior analysis from a set of corporal language vocabulary. In this work, we present our achievements characterizing some simple behaviors from visual data on different real applications and discuss our plan for future work: low level vocabulary definition from bag-of-gesture units and high level modelling and inference of human behaviors.
	Address	Barcelona
	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	978-1-57735-516-8	Medium
	Area		Expedition		Conference	IJCAI
	Notes	HuPBA;MV			Approved	no
	Call Number	Admin @ si @ PGB2011b			Serial	1770
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	Author	Jürgen Brauer; Wenjuan Gong; Jordi Gonzalez; Michael Arens
	Title	On the Effect of Temporal Information on Monocular 3D Human Pose Estimation			Type	Conference Article
	Year	2011	Publication	2nd IEEE International Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams	Abbreviated Journal
	Volume		Issue		Pages	906 - 913
	Keywords
	Abstract	We address the task of estimating 3D human poses from monocular camera sequences. Many works make use of multiple consecutive frames for the estimation of a 3D pose in a frame. Although such an approach should ease the pose estimation task substantially since multiple consecutive frames allow to solve for 2D projection ambiguities in principle, it has not yet been investigated systematically how much we can improve the 3D pose estimates when using multiple consecutive frames opposed to single frame information. In this paper we analyze the difference in quality of 3D pose estimates based on different numbers of consecutive frames from which 2D pose estimates are available. We validate the use of temporal information on two major different approaches for human pose estimation – modeling and learning approaches. The results of our experiments show that both learning and modeling approaches benefit from using multiple frames opposed to single frame input but that the benefit is small when the 2D pose estimates show a high quality in terms of precision.
	Address	Barcelona
	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	978-1-4673-0062-9	Medium
	Area		Expedition		Conference	ARTEMIS
	Notes	ISE			Approved	no
	Call Number	Admin @ si @BGG 2011			Serial	1860
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	Author	Antonio Hernandez; Carlos Primo; Sergio Escalera
	Title	Automatic user interaction correction via Multi-label Graph cuts			Type	Conference Article
	Year	2011	Publication	In ICCV 2011 1st IEEE International Workshop on Human Interaction in Computer Vision HICV	Abbreviated Journal
	Volume		Issue		Pages	1276-1281
	Keywords
	Abstract	Most applications in image segmentation requires from user interaction in order to achieve accurate results. However, user wants to achieve the desired segmentation accuracy reducing effort of manual labelling. In this work, we extend standard multi-label α-expansion Graph Cut algorithm so that it analyzes the interaction of the user in order to modify the object model and improve final segmentation of objects. The approach is inspired in the fact that fast user interactions may introduce some pixel errors confusing object and background. Our results with different degrees of user interaction and input errors show high performance of the proposed approach on a multi-label human limb segmentation problem compared with classical α-expansion algorithm.
	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	978-1-4673-0062-9	Medium
	Area		Expedition		Conference	HICV
	Notes	MILAB; HuPBA			Approved	no
	Call Number	Admin @ si @ HPE2011			Serial	1892
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	Author	Miguel Reyes; Gabriel Dominguez; Sergio Escalera
	Title	Feature Weighting in Dynamic Time Warping for Gesture Recognition in Depth Data			Type	Conference Article
	Year	2011	Publication	1st IEEE Workshop on Consumer Depth Cameras for Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	1182-1188
	Keywords
	Abstract	We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping approach.
	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	978-1-4673-0062-9	Medium
	Area		Expedition		Conference	CDC4CV
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ RDE2011			Serial	1893
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	Author	Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados; Thierry Brouard
	Title	Subgraph Spotting Through Explicit Graph Embedding: An Application to Content Spotting in Graphic Document Images			Type	Conference Article
	Year	2011	Publication	11th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	870-874
	Keywords
	Abstract	We present a method for spotting a subgraph in a graph repository. Subgraph spotting is a very interesting research problem for various application domains where the use of a relational data structure is mandatory. Our proposed method accomplishes subgraph spotting through graph embedding. We achieve automatic indexation of a graph repository during off-line learning phase, where we (i) break the graphs into 2-node sub graphs (a.k.a. cliques of order 2), which are primitive building-blocks of a graph, (ii) embed the 2-node sub graphs into feature vectors by employing our recently proposed explicit graph embedding technique, (iii) cluster the feature vectors in classes by employing a classic agglomerative clustering technique, (iv) build an index for the graph repository and (v) learn a Bayesian network classifier. The subgraph spotting is achieved during the on-line querying phase, where we (i) break the query graph into 2-node sub graphs, (ii) embed them into feature vectors, (iii) employ the Bayesian network classifier for classifying the query 2-node sub graphs and (iv) retrieve the respective graphs by looking-up in the index of the graph repository. The graphs containing all query 2-node sub graphs form the set of result graphs for the query. Finally, we employ the adjacency matrix of each result graph along with a score function, for spotting the query graph in it. The proposed subgraph spotting method is equally applicable to a wide range of domains, offering ease of query by example (QBE) and granularity of focused retrieval. Experimental results are presented for graphs generated from two repositories of electronic and architectural document images.
	Address	Beijing, China
	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	1520-5363	ISBN	978-1-4577-1350-7	Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ LRL2011			Serial	1790
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	Author	Anjan Dutta; Josep Llados; Umapada Pal
	Title	Symbol Spotting in Line Drawings Through Graph Paths Hashing			Type	Conference Article
	Year	2011	Publication	11th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	982-986
	Keywords
	Abstract	In this paper we propose a symbol spotting technique through hashing the shape descriptors of graph paths (Hamiltonian paths). Complex graphical structures in line drawings can be efficiently represented by graphs, which ease the accurate localization of the model symbol. Graph paths are the factorized substructures of graphs which enable robust recognition even in the presence of noise and distortion. In our framework, the entire database of the graphical documents is indexed in hash tables by the locality sensitive hashing (LSH) of shape descriptors of the paths. The hashing data structure aims to execute an approximate k-NN search in a sub-linear time. The spotting method is formulated by a spatial voting scheme to the list of locations of the paths that are decided during the hash table lookup process. We perform detailed experiments with various dataset of line drawings and the results demonstrate the effectiveness and efficiency of the technique.
	Address	Beijing, China
	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	1520-5363	ISBN	978-1-4577-1350-7	Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ DLP2011b			Serial	1791
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