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	Author	Bogdan Raducanu; Fadi Dornaika
	Title	Texture-independent recognition of facial expressions in image snapshots and videos			Type	Journal Article
	Year	2013	Publication	Machine Vision and Applications	Abbreviated Journal	MVA
	Volume	24	Issue	4	Pages	811-820
	Keywords
	Abstract	This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines.
	Address
	Corporate Author				Thesis
	Publisher	Springer-Verlag	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0932-8092	ISBN		Medium
	Area		Expedition		Conference
	Notes	OR; 600.046; 605.203;MV			Approved	no
	Call Number	Admin @ si @ RaD2013			Serial	2230
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	Author	Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg
	Title	Coloring Action Recognition in Still Images			Type	Journal Article
	Year	2013	Publication	International Journal of Computer Vision	Abbreviated Journal	IJCV
	Volume	105	Issue	3	Pages	205-221
	Keywords
	Abstract	In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification.
	Address
	Corporate Author				Thesis
	Publisher	Springer US	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0920-5691	ISBN		Medium
	Area		Expedition		Conference
	Notes	CIC; ADAS; 600.057; 600.048			Approved	no
	Call Number	Admin @ si @ KRW2013			Serial	2285
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	Author	Naveen Onkarappa; Angel Sappa
	Title	A Novel Space Variant Image Representation			Type	Journal Article
	Year	2013	Publication	Journal of Mathematical Imaging and Vision	Abbreviated Journal	JMIV
	Volume	47	Issue	1-2	Pages	48-59
	Keywords	Space-variant representation; Log-polar mapping; Onboard vision applications
	Abstract	Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences.
	Address
	Corporate Author				Thesis
	Publisher	Springer US	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0924-9907	ISBN		Medium
	Area		Expedition		Conference
	Notes	ADAS; 600.055; 605.203; 601.215			Approved	no
	Call Number	Admin @ si @ OnS2013a			Serial	2243
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	Author	Mariella Dimiccoli; Benoît Girard; Alain Berthoz; Daniel Bennequin
	Title	Striola Magica: a functional explanation of otolith organs			Type	Journal Article
	Year	2013	Publication	Journal of Computational Neuroscience	Abbreviated Journal	JCN
	Volume	35	Issue	2	Pages	125-154
	Keywords	Otolith organs ;Striola; Vestibular pathway
	Abstract	Otolith end organs of vertebrates sense linear accelerations of the head and gravitation. The hair cells on their epithelia are responsible for transduction. In mammals, the striola, parallel to the line where hair cells reverse their polarization, is a narrow region centered on a curve with curvature and torsion. It has been shown that the striolar region is functionally different from the rest, being involved in a phasic vestibular pathway. We propose a mathematical and computational model that explains the necessity of this amazing geometry for the striola to be able to carry out its function. Our hypothesis, related to the biophysics of the hair cells and to the physiology of their afferent neurons, is that striolar afferents collect information from several type I hair cells to detect the jerk in a large domain of acceleration directions. This predicts a mean number of two calyces for afferent neurons, as measured in rodents. The domain of acceleration directions sensed by our striolar model is compatible with the experimental results obtained on monkeys considering all afferents. Therefore, the main result of our study is that phasic and tonic vestibular afferents cover the same geometrical fields, but at different dynamical and frequency domains.
	Address
	Corporate Author				Thesis
	Publisher	Springer US	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1573-6873. 2013	ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @DBG2013			Serial	2787
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	Author	Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados
	Title	Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces			Type	Book Chapter
	Year	2013	Publication	Graph Embedding for Pattern Analysis	Abbreviated Journal
	Volume		Issue		Pages	1-26
	Keywords
	Abstract	Ability to recognize patterns is among the most crucial capabilities of human beings for their survival, which enables them to employ their sophisticated neural and cognitive systems [1], for processing complex audio, visual, smell, touch, and taste signals. Man is the most complex and the best existing system of pattern recognition. Without any explicit thinking, we continuously compare, classify, and identify huge amount of signal data everyday [2], starting from the time we get up in the morning till the last second we fall asleep. This includes recognizing the face of a friend in a crowd, a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis.
	Address
	Corporate Author				Thesis
	Publisher	Springer New York	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4614-4456-5	Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ LRL2013b			Serial	2271
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	Author	Miquel Ferrer; I. Bardaji; Ernest Valveny; Dimosthenis Karatzas; Horst Bunke
	Title	Median Graph Computation by Means of Graph Embedding into Vector Spaces			Type	Book Chapter
	Year	2013	Publication	Graph Embedding for Pattern Analysis	Abbreviated Journal
	Volume		Issue		Pages	45-72
	Keywords
	Abstract	In pattern recognition [8, 14], a key issue to be addressed when designing a system is how to represent input patterns. Feature vectors is a common option. That is, a set of numerical features describing relevant properties of the pattern are computed and arranged in a vector form. The main advantages of this kind of representation are computational simplicity and a well sound mathematical foundation. Thus, a large number of operations are available to work with vectors and a large repository of algorithms for pattern analysis and classification exist. However, the simple structure of feature vectors might not be the best option for complex patterns where nonnumerical features or relations between different parts of the pattern become relevant.
	Address
	Corporate Author				Thesis
	Publisher	Springer New York	Place of Publication		Editor	Yun Fu; Yungian Ma
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4614-4456-5	Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ FBV2013			Serial	2421
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	Author	Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca
	Title	Towards Ontological Cognitive System			Type	Book Chapter
	Year	2013	Publication	Topics in Medical Image Processing and Computational Vision	Abbreviated Journal
	Volume	8	Issue		Pages	87-99
	Keywords
	Abstract	The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users.
	Address
	Corporate Author				Thesis
	Publisher	Springer Netherlands	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	2212-9391	ISBN	978-94-007-0725-2	Medium
	Area		Expedition		Conference
	Notes	ISE; 605.203; 302.018; 600.049			Approved	no
	Call Number	Admin @ si @ FGT2013			Serial	2287
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	Author	Patricia Marquez; Debora Gil; Aura Hernandez-Sabate; Daniel Kondermann
	Title	When Is A Confidence Measure Good Enough?			Type	Conference Article
	Year	2013	Publication	9th International Conference on Computer Vision Systems	Abbreviated Journal
	Volume	7963	Issue		Pages	344-353
	Keywords	Optical flow, confidence measure, performance evaluation
	Abstract	Confidence estimation has recently become a hot topic in image processing and computer vision.Yet, several definitions exist of the term “confidence” which are sometimes used interchangeably. This is a position paper, in which we aim to give an overview on existing definitions, thereby clarifying the meaning of the used terms to facilitate further research in this field. Based on these clarifications, we develop a theory to compare confidence measures with respect to their quality.
	Address	St Petersburg; Russia; July 2013
	Corporate Author				Thesis
	Publisher	Springer Link	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	978-3-642-39401-0	Medium
	Area		Expedition		Conference	ICVS
	Notes	IAM;ADAS; 600.044; 600.057; 600.060; 601.145			Approved	no
	Call Number	IAM @ iam @ MGH2013a			Serial	2218
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	Author	Alex Pardo; Albert Clapes; Sergio Escalera; Oriol Pujol
	Title	Actions in Context: System for people with Dementia			Type	Conference Article
	Year	2013	Publication	2nd International Workshop on Citizen Sensor Networks (Citisen2013) at the European Conference on Complex Systems	Abbreviated Journal
	Volume		Issue		Pages	3-14
	Keywords	Multi-modal data Fusion; Computer vision; Wearable sensors; Gesture recognition; Dementia
	Abstract	In the next forty years, the number of people living with dementia is expected to triple. In the last stages, people affected by this disease become dependent. This hinders the autonomy of the patient and has a huge social impact in time, money and effort. Given this scenario, we propose an ubiquitous system capable of recognizing daily specific actions. The system fuses and synchronizes data obtained from two complementary modalities – ambient and egocentric. The ambient approach consists in a fixed RGB-Depth camera for user and object recognition and user-object interaction, whereas the egocentric point of view is given by a personal area network (PAN) formed by a few wearable sensors and a smartphone, used for gesture recognition. The system processes multi-modal data in real-time, performing paralleled task recognition and modality synchronization, showing high performance recognizing subjects, objects, and interactions, showing its reliability to be applied in real case scenarios.
	Address	Barcelona; September 2013
	Corporate Author				Thesis
	Publisher	Springer International Publishing	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-319-04177-3	Medium
	Area		Expedition		Conference	ECCS
	Notes	HUPBA;MILAB			Approved	no
	Call Number	Admin @ si @ PCE2013			Serial	2354
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	Author	Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu
	Title	Efficient Graph Construction for Label Propagation based Multi-observation Face Recognition			Type	Conference Article
	Year	2013	Publication	Human Behavior Understanding 4th International Workshop	Abbreviated Journal
	Volume	8212	Issue		Pages	124-135
	Keywords
	Abstract	Workshop on Human Behavior Understanding Human-machine interaction is a hot topic nowadays in the communities of multimedia and computer vision. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. Recently, graph-based label propagation for multi-observation face recognition was proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot adapt optimally to the data. In this paper, we propose a novel approach for efficient and adaptive graph construction that can be used for multi-observation face recognition as well as for other recognition problems. Experimental results performed on Honda video face database, show a distinct advantage of the proposed method over the standard graph construction methods.
	Address	Barcelona
	Corporate Author				Thesis
	Publisher	Springer International Publishing	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-319-02713-5	Medium
	Area		Expedition		Conference	HBU
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ DBR2013			Serial	2315
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	Author	Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez
	Title	On-line lumen centre detection in gastrointestinal and respiratory endoscopy			Type	Conference Article
	Year	2013	Publication	Second International Workshop Clinical Image-Based Procedures	Abbreviated Journal
	Volume	8361	Issue		Pages	31-38
	Keywords	Lumen centre detection; Bronchoscopy; Colonoscopy
	Abstract	We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %).
	Address	Nagoya; Japan; September 2013
	Corporate Author				Thesis
	Publisher	Springer International Publishing	Place of Publication		Editor	Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-319-05665-4	Medium
	Area	800	Expedition		Conference	CLIP
	Notes	MV; IAM; 600.047; 600.044; 600.060			Approved	no
	Call Number	Admin @ si @ SBG2013			Serial	2302
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	Author	Francesco Ciompi; Rui Hua; Simone Balocco; Marina Alberti; Oriol Pujol; Carles Caus; J. Mauri; Petia Radeva
	Title	Learning to Detect Stent Struts in Intravascular Ultrasound			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	575-583
	Keywords
	Abstract	In this paper we tackle the automatic detection of struts elements (metallic braces of a stent device) in Intravascular Ultrasound (IVUS) sequences. The proposed method is based on context-aware classification of IVUS images, where we use Multi-Class Multi-Scale Stacked Sequential Learning (M2SSL). Additionally, we introduce a novel technique to reduce the amount of required contextual features. The comparison with binary and multi-class learning is also performed, using a dataset of IVUS images with struts manually annotated by an expert. The best performing configuration reaches a F-measure F = 63.97% .
	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
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-38627-5	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	MILAB; HuPBA; 605.203; 600.046			Approved	no
	Call Number	Admin @ si @ CHB2013			Serial	2349
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	Author	Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol
	Title	Interactive Document Retrieval and Classification.			Type	Book Chapter
	Year	2013	Publication	Multimodal Interaction in Image and Video Applications	Abbreviated Journal
	Volume	48	Issue		Pages	17-30
	Keywords
	Abstract	In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	Angel Sappa; Jordi Vitria
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1868-4394	ISBN	978-3-642-35931-6	Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ VRM2013			Serial	2341
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	Author	Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Bemedi
	Title	Page Segmentation of Structured Documents Using 2D Stochastic Context-Free Grammars			Type	Conference Article
	Year	2013	Publication	6th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	7887	Issue		Pages	133-140
	Keywords
	Abstract	In this paper we define a bidimensional extension of Stochastic Context-Free Grammars for page segmentation of structured documents. Two sets of text classification features are used to perform an initial classification of each zone of the page. Then, the page segmentation is obtained as the most likely hypothesis according to a grammar. This approach is compared to Conditional Random Fields and results show significant improvements in several cases. Furthermore, grammars provide a detailed segmentation that allowed a semantic evaluation which also validates this model.
	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; 605.203			Approved	no
	Call Number	Admin @ si @ ACS2013			Serial	2328
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	Author	Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny
	Title	Notation-invariant patch-based wall detector in architectural floor plans			Type	Book Chapter
	Year	2013	Publication	Graphics Recognition. New Trends and Challenges	Abbreviated Journal
	Volume	7423	Issue		Pages	79--88
	Keywords
	Abstract	Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper.
	Address
	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	978-3-642-36823-3	Medium
	Area		Expedition		Conference
	Notes	DAG; 600.045; 600.056; 605.203			Approved	no
	Call Number	Admin @ si @ HMS2013			Serial	2322
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