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	Author	Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva
	Title	Text Detection in Urban Scenes (video sample)			Type	Conference Article
	Year	2009	Publication	12th International Conference of the Catalan Association for Artificial Intelligence	Abbreviated Journal
	Volume	202	Issue		Pages	35–44
	Keywords
	Abstract	Abstract. Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are just a few problems. Text detection can be specially suited for georeferencing business, navigation, tourist assistance, or to help visual impaired people. In this paper, we propose a general methodology to deal with the problem of text detection in outdoor scenes. The method is based on learning spatial information of gradient based features and Census Transform images using a cascade of classifiers. The method is applied in the context of Mobile Mapping systems, where a mobile vehicle captures urban image sequences. Moreover, a cover data set is presented and tested with the new methodology. The results show high accuracy when detecting multi-linear text regions with high variability of appearance, at same time that it preserves a low false alarm rate compared to classical approaches
	Address	Cardona (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	978-1-60750-061-2	Medium
	Area		Expedition		Conference	CCIA
	Notes	OR;MILAB;HuPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ EBV2009			Serial	1181
Permanent link to this record



	Author	Sergio Escalera; Oriol Pujol; Petia Radeva; Jordi Vitria
	Title	Measuring Interest of Human Dyadic Interactions			Type	Conference Article
	Year	2009	Publication	12th International Conference of the Catalan Association for Artificial Intelligence	Abbreviated Journal
	Volume	202	Issue		Pages	45-54
	Keywords
	Abstract	In this paper, we argue that only using behavioural motion information, we are able to predict the interest of observers when looking at face-to-face interactions. We propose a set of movement-related features from body, face, and mouth activity in order to define a set of higher level interaction features, such as stress, activity, speaking engagement, and corporal engagement. Error-Correcting Output Codes framework with an Adaboost base classifier is used to learn to rank the perceived observer's interest in face-to-face interactions. The automatic system shows good correlation between the automatic categorization results and the manual ranking made by the observers. In particular, the learning system shows that stress features have a high predictive power for ranking interest of observers when looking at of face-to-face interactions.
	Address	Cardona (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	978-1-60750-061-2	Medium
	Area		Expedition		Conference	CCIA
	Notes	OR;MILAB;HuPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ EPR2009b			Serial	1182
Permanent link to this record



	Author	Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria
	Title	Generic Object Recognition in Urban Image Databases			Type	Conference Article
	Year	2009	Publication	12th International Conference of the Catalan Association for Artificial Intelligence	Abbreviated Journal
	Volume	202	Issue		Pages	27-34
	Keywords
	Abstract	In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (>500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. All this information is extracted without an object of reference, which allows to search for any type of objects using their visual appearance. A new Visual Content layer is built over Google Maps, allowing the object recognition information to be organized and fused with other content, like satellite images, street maps, and business locations.
	Address	Cardona (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	978-1-60750-061-2	Medium
	Area		Expedition		Conference	CCIA
	Notes	OR;MILAB;HuPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VER2009			Serial	1183
Permanent link to this record



	Author	Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria
	Title	Visual Content Layer for Scalable Recognition in Urban Image Databases, Internet Multimedia Search and Mining			Type	Conference Article
	Year	2009	Publication	10th IEEE International Conference on Multimedia and Expo	Abbreviated Journal
	Volume		Issue		Pages	1616–1619
	Keywords
	Abstract	Rich online map interaction represents a useful tool to get multimedia information related to physical places. With this type of systems, users can automatically compute the optimal route for a trip or to look for entertainment places or hotels near their actual position. Standard maps are defined as a fusion of layers, where each one contains specific data such height, streets, or a particular business location. In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (> 500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. This allows an efficient and scalable way of accessing maps by visual content.
	Address	New York (USA)
	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	978-1-4244-4291-1	Medium
	Area		Expedition		Conference	ICME
	Notes	OR;MILAB;HuPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ BER2009			Serial	1189
Permanent link to this record



	Author	Pierluigi Casale; Oriol Pujol; Petia Radeva; Jordi Vitria
	Title	A First Approach to Activity Recognition Using Topic Models			Type	Conference Article
	Year	2009	Publication	12th International Conference of the Catalan Association for Artificial Intelligence	Abbreviated Journal
	Volume	202	Issue		Pages	74 - 82
	Keywords
	Abstract	In this work, we present a first approach to activity patterns discovery by mean of topic models. Using motion data collected with a wearable device we prototype, TheBadge, we analyse raw accelerometer data using Latent Dirichlet Allocation (LDA), a particular instantiation of topic models. Results show that for particular values of the parameters necessary for applying LDA to a countinous dataset, good accuracies in activity classification can be achieved.
	Address	Cardona, 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	978-1-60750-061-2	Medium
	Area		Expedition		Conference	CCIA
	Notes	OR;MILAB;HuPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ CPR2009e			Serial	1231
Permanent link to this record



	Author	Fosca De Iorio; Carolina Malagelada; Fernando Azpiroz; M. Maluenda; C. Violanti; Laura Igual; Jordi Vitria; Juan R. Malagelada
	Title	Intestinal motor activity, endoluminal motion and transit			Type	Journal Article
	Year	2009	Publication	Neurogastroenterology & Motility	Abbreviated Journal	NEUMOT
	Volume	21	Issue	12	Pages	1264–e119
	Keywords
	Abstract	A programme for evaluation of intestinal motility has been recently developed based on endoluminal image analysis using computer vision methodology and machine learning techniques. Our aim was to determine the effect of intestinal muscle inhibition on wall motion, dynamics of luminal content and transit in the small bowel. Fourteen healthy subjects ingested the endoscopic capsule (Pillcam, Given Imaging) in fasting conditions. Seven of them received glucagon (4.8 microg kg(-1) bolus followed by a 9.6 microg kg(-1) h(-1) infusion during 1 h) and in the other seven, fasting activity was recorded, as controls. This dose of glucagon has previously shown to inhibit both tonic and phasic intestinal motor activity. Endoluminal image and displacement was analyzed by means of a computer vision programme specifically developed for the evaluation of muscular activity (contractile and non-contractile patterns), intestinal contents, endoluminal motion and transit. Thirty-minute periods before, during and after glucagon infusion were analyzed and compared with equivalent periods in controls. No differences were found in the parameters measured during the baseline (pretest) periods when comparing glucagon and control experiments. During glucagon infusion, there was a significant reduction in contractile activity (0.2 +/- 0.1 vs 4.2 +/- 0.9 luminal closures per min, P < 0.05; 0.4 +/- 0.1 vs 3.4 +/- 1.2% of images with radial wrinkles, P < 0.05) and a significant reduction of endoluminal motion (82 +/- 9 vs 21 +/- 10% of static images, P < 0.05). Endoluminal image analysis, by means of computer vision and machine learning techniques, can reliably detect reduced intestinal muscle activity and motion.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MILAB;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ DMA2009			Serial	1251
Permanent link to this record



	Author	Bogdan Raducanu; Jordi Vitria; D. Gatica-Perez
	Title	You are Fired! Nonverbal Role Analysis in Competitive Meetings			Type	Conference Article
	Year	2009	Publication	IEEE International Conference on Audio, Speech and Signal Processing	Abbreviated Journal
	Volume		Issue		Pages	1949–1952
	Keywords
	Abstract	This paper addresses the problem of social interaction analysis in competitive meetings, using nonverbal cues. For our study, we made use of ldquoThe Apprenticerdquo reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status and predicting the fired candidates. The current study was carried out using nonverbal audio cues. Results obtained from the analysis of a full season of the show, representing around 90 minutes of audio data, are very promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words.
	Address	Taipei, Taiwan
	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	1520-6149	ISBN	978-1-4244-2353-8	Medium
	Area		Expedition		Conference	ICASSP
	Notes	OR;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ RVG2009			Serial	1154
Permanent link to this record



	Author	David Masip; Agata Lapedriza; Jordi Vitria
	Title	Boosted Online Learning for Face Recognition			Type	Journal Article
	Year	2009	Publication	IEEE Transactions on Systems, Man and Cybernetics part B	Abbreviated Journal	TSMCB
	Volume	39	Issue	2	Pages	530–538
	Keywords
	Abstract	Face recognition applications commonly suffer from three main drawbacks: a reduced training set, information lying in high-dimensional subspaces, and the need to incorporate new people to recognize. In the recent literature, the extension of a face classifier in order to include new people in the model has been solved using online feature extraction techniques. The most successful approaches of those are the extensions of the principal component analysis or the linear discriminant analysis. In the current paper, a new online boosting algorithm is introduced: a face recognition method that extends a boosting-based classifier by adding new classes while avoiding the need of retraining the classifier each time a new person joins the system. The classifier is learned using the multitask learning principle where multiple verification tasks are trained together sharing the same feature space. The new classes are added taking advantage of the structure learned previously, being the addition of new classes not computationally demanding. The present proposal has been (experimentally) validated with two different facial data sets by comparing our approach with the current state-of-the-art techniques. The results show that the proposed online boosting algorithm fares better in terms of final accuracy. In addition, the global performance does not decrease drastically even when the number of classes of the base problem is multiplied by eight.
	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	1083–4419	ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ MLV2009			Serial	1155
Permanent link to this record



	Author	D. Jayagopi; Bogdan Raducanu; D. Gatica-Perez
	Title	Characterizing conversational group dynamics using nonverbal behaviour			Type	Conference Article
	Year	2009	Publication	10th IEEE International Conference on Multimedia and Expo	Abbreviated Journal
	Volume		Issue		Pages	370–373
	Keywords
	Abstract	This paper addresses the novel problem of characterizing conversational group dynamics. It is well documented in social psychology that depending on the objectives a group, the dynamics are different. For example, a competitive meeting has a different objective from that of a collaborative meeting. We propose a method to characterize group dynamics based on the joint description of a group members' aggregated acoustical nonverbal behaviour to classify two meeting datasets (one being cooperative-type and the other being competitive-type). We use 4.5 hours of real behavioural multi-party data and show that our methodology can achieve a classification rate of upto 100%.
	Address	New York, USA
	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	978-1-4244-4290-4	Medium
	Area		Expedition		Conference	ICME
	Notes	OR;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ JRG2009			Serial	1217
Permanent link to this record



	Author	Fadi Dornaika; Bogdan Raducanu
	Title	Three-Dimensional Face Pose Detection and Tracking Using Monocular Videos: Tool and Application			Type	Journal Article
	Year	2009	Publication	IEEE Transactions on Systems, Man and Cybernetics part B	Abbreviated Journal	TSMCB
	Volume	39	Issue	4	Pages	935–944
	Keywords
	Abstract	Recently, we have proposed a real-time tracker that simultaneously tracks the 3-D head pose and facial actions in monocular video sequences that can be provided by low quality cameras. This paper has two main contributions. First, we propose an automatic 3-D face pose initialization scheme for the real-time tracker by adopting a 2-D face detector and an eigenface system. Second, we use the proposed methods-the initialization and tracking-for enhancing the human-machine interaction functionality of an AIBO robot. More precisely, we show how the orientation of the robot's camera (or any active vision system) can be controlled through the estimation of the user's head pose. Applications based on head-pose imitation such as telepresence, virtual reality, and video games can directly exploit the proposed techniques. Experiments on real videos confirm the robustness and usefulness of the proposed methods.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ DoR2009a			Serial	1218
Permanent link to this record



	Author	Fadi Dornaika; Bogdan Raducanu
	Title	Simultaneous 3D face pose and person-specific shape estimation from a single image using a holistic approach			Type	Conference Article
	Year	2009	Publication	IEEE Workshop on Applications of Computer Vision	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	This paper presents a new approach for the simultaneous estimation of the 3D pose and specific shape of a previously unseen face from a single image. The face pose is not limited to a frontal view. We describe a holistic approach based on a deformable 3D model and a learned statistical facial texture model. Rather than obtaining a person-specific facial surface, the goal of this work is to compute person-specific 3D face shape in terms of a few control parameters that are used by many applications. The proposed holistic approach estimates the 3D pose parameters as well as the face shape control parameters by registering the warped texture to a statistical face texture, which is carried out by a stochastic and genetic optimizer. The proposed approach has several features that make it very attractive: (i) it uses a single grey-scale image, (ii) it is person-independent, (iii) it is featureless (no facial feature extraction is required), and (iv) its learning stage is easy. The proposed approach lends itself nicely to 3D face tracking and face gesture recognition in monocular videos. We describe extensive experiments that show the feasibility and robustness of the proposed approach.
	Address	Utah, USA
	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	1550-5790	ISBN	978-1-4244-5497-6	Medium
	Area		Expedition		Conference	WACV
	Notes	OR;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ DoR2009b			Serial	1256
Permanent link to this record



	Author	Bogdan Raducanu; Fadi Dornaika
	Title	Natural Facial Expression Recognition Using Dynamic and Static Schemes			Type	Conference Article
	Year	2009	Publication	5th International Symposium on Visual Computing	Abbreviated Journal
	Volume	5875	Issue		Pages	730–739
	Keywords
	Abstract	Affective computing is at the core of a new paradigm in HCI and AI represented by human-centered computing. Within this paradigm, it is expected that machines will be enabled with perceiving capabilities, making them aware about users’ affective state. The current paper addresses the problem of facial expression recognition from monocular videos sequences. We propose a dynamic facial expression recognition scheme, which is proven to be very efficient. Furthermore, it is conveniently compared with several static-based systems adopting different magnitude of facial expression. We provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). We also provide performance evaluations using arbitrary test video sequences.
	Address	Las Vegas, USA
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-10330-8	Medium
	Area		Expedition		Conference	ISVC
	Notes	OR;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ RaD2009			Serial	1257
Permanent link to this record



	Author	Agata Lapedriza
	Title	Multitask Learning Techniques for Automatic Face Classification			Type	Book Whole
	Year	2009	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Automatic face classification is currently a popular research area in Computer Vision. It involves several subproblems, such as subject recognition, gender classification or subject verification. Current systems of automatic face classification need a large amount of training data to robustly learn a task. However, the collection of labeled data is usually a difficult issue. For this reason, the research on methods that are able to learn from a small sized training set is essential. The dependency on the abundance of training data is not so evident in human learning processes. We are able to learn from a very small number of examples, given that we use, additionally, some prior knowledge to learn a new task. For example, we frequently find patterns and analogies from other domains to reuse them in new situations, or exploit training data from other experiences. In computer science, Multitask Learning is a new Machine Learning approach that studies this idea of knowledge transfer among different tasks, to overcome the effects of the small sample sized problem. This thesis explores, proposes and tests some Multitask Learning methods specially developed for face classification purposes. Moreover, it presents two more contributions dealing with the small sample sized problem, out of the Multitask Learning context. The first one is a method to extract external face features, to be used as an additional information source in automatic face classification problems. The second one is an empirical study on the most suitable face image resolution to perform automatic subject recognition.
	Address	Barcelona (Spain)
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	Ediciones Graficas Rey	Place of Publication		Editor	Jordi Vitria;David Masip
	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 @ Lap2009			Serial	1263
Permanent link to this record



	Author	Daniel Ponsa; Antonio Lopez
	Title	Seguimiento Visual de Contornos Computerizado			Type	Miscellaneous
	Year	2009	Publication	UAB Divulga, Revista de divulgacion cientifica	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	spreading;ADAS			Approved	no
	Call Number	ADAS @ adas @ PoL2009b			Serial	1270
Permanent link to this record