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	Author	Jose Manuel Alvarez; Theo Gevers; Y. LeCun; Antonio Lopez
	Title	Road Scene Segmentation from a Single Image			Type	Conference Article
	Year	2012	Publication	12th European Conference on Computer Vision	Abbreviated Journal
	Volume	7578	Issue	VII	Pages	376-389
	Keywords	road detection
	Abstract	Road scene segmentation is important in computer vision for different applications such as autonomous driving and pedestrian detection. Recovering the 3D structure of road scenes provides relevant contextual information to improve their understanding. In this paper, we use a convolutional neural network based algorithm to learn features from noisy labels to recover the 3D scene layout of a road image. The novelty of the algorithm relies on generating training labels by applying an algorithm trained on a general image dataset to classify on–board images. Further, we propose a novel texture descriptor based on a learned color plane fusion to obtain maximal uniformity in road areas. Finally, acquired (off–line) and current (on–line) information are combined to detect road areas in single images. From quantitative and qualitative experiments, conducted on publicly available datasets, it is concluded that convolutional neural networks are suitable for learning 3D scene layout from noisy labels and provides a relative improvement of 7% compared to the baseline. Furthermore, combining color planes provides a statistical description of road areas that exhibits maximal uniformity and provides a relative improvement of 8% compared to the baseline. Finally, the improvement is even bigger when acquired and current information from a single image are combined
	Address	Florence, Italy
	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	978-3-642-33785-7	Medium
	Area		Expedition		Conference	ECCV
	Notes	ADAS;ISE			Approved	no
	Call Number	Admin @ si @ AGL2012; ADAS @ adas @ agl2012a			Serial	2022
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	Author	Ivo Everts; Jan van Gemert; Theo Gevers
	Title	Per-patch Descriptor Selection using Surface and Scene Properties			Type	Conference Article
	Year	2012	Publication	12th European Conference on Computer Vision	Abbreviated Journal
	Volume	7577	Issue	VI	Pages	172-186
	Keywords
	Abstract	Local image descriptors are generally designed for describing all possible image patches. Such patches may be subject to complex variations in appearance due to incidental object, scene and recording conditions. Because of this, a single-best descriptor for accurate image representation under all conditions does not exist. Therefore, we propose to automatically select from a pool of descriptors the one that is best suitable based on object surface and scene properties. These properties are measured on the fly from a single image patch through a set of attributes. Attributes are input to a classifier which selects the best descriptor. Our experiments on a large dataset of colored object patches show that the proposed selection method outperforms the best single descriptor and a-priori combinations of the descriptor pool.
	Address	Florence, Italy
	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	978-3-642-33782-6	Medium
	Area		Expedition		Conference	ECCV
	Notes	ALTRES;ISE			Approved	no
	Call Number	Admin @ si @ EGG2012			Serial	2023
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	Author	Hamdi Dibeklioglu; Theo Gevers; Albert Ali Salah
	Title	Are You Really Smiling at Me? Spontaneous versus Posed Enjoyment Smiles			Type	Conference Article
	Year	2012	Publication	12th European Conference on Computer Vision	Abbreviated Journal
	Volume	7574	Issue	III	Pages	525-538
	Keywords
	Abstract	Smiling is an indispensable element of nonverbal social interaction. Besides, automatic distinction between spontaneous and posed expressions is important for visual analysis of social signals. Therefore, in this paper, we propose a method to distinguish between spontaneous and posed enjoyment smiles by using the dynamics of eyelid, cheek, and lip corner movements. The discriminative power of these movements, and the effect of different fusion levels are investigated on multiple databases. Our results improve the state-of-the-art. We also introduce the largest spontaneous/posed enjoyment smile database collected to date, and report new empirical and conceptual findings on smile dynamics. The collected database consists of 1240 samples of 400 subjects. Moreover, it has the unique property of having an age range from 8 to 76 years. Large scale experiments on the new database indicate that eyelid dynamics are highly relevant for smile classification, and there are age-related differences in smile dynamics.
	Address	Florence, Italy
	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	978-3-642-33711-6	Medium
	Area		Expedition		Conference	ECCV
	Notes	ALTRES;ISE			Approved	no
	Call Number	Admin @ si @ DGS2012			Serial	2024
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	Author	Ricard Borras; Agata Lapedriza; Laura Igual
	Title	Depth Information in Human Gait Analysis: An Experimental Study on Gender Recognition			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7325	Issue	II	Pages	98-105
	Keywords
	Abstract	This work presents DGait, a new gait database acquired with a depth camera. This database contains videos from 53 subjects walking in different directions. The intent of this database is to provide a public set to explore whether the depth can be used as an additional information source for gait classification purposes. Each video is labelled according to subject, gender and age. Furthermore, for each subject and view point, we provide initial and final frames of an entire walk cycle. On the other hand, we perform gait-based gender classification experiments with DGait database, in order to illustrate the usefulness of depth information for this purpose. In our experiments, we extract 2D and 3D gait features based on shape descriptors, and compare the performance of these features for gender identification, using a Kernel SVM. The obtained results show that depth can be an information source of great relevance for gait classification problems.
	Address	Aveiro, Portugal
	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	978-3-642-31297-7	Medium
	Area		Expedition		Conference	ICIAR
	Notes	OR; MILAB;MV			Approved	no
	Call Number	Admin @ si @ BLI2012			Serial	2009
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	Author	Laura Igual; Joan Carles Soliva; Roger Gimeno; Sergio Escalera; Oscar Vilarroya; Petia Radeva
	Title	Automatic Internal Segmentation of Caudate Nucleus for Diagnosis of Attention Deficit Hyperactivity Disorder			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7325	Issue	II	Pages	222-229
	Keywords
	Abstract	Poster Studies on volumetric brain Magnetic Resonance Imaging (MRI) showed neuroanatomical abnormalities in pediatric Attention-Deficit/Hyperactivity Disorder (ADHD). In particular, the diminished right caudate volume is one of the most replicated findings among ADHD samples in morphometric MRI studies. In this paper, we propose a fully-automatic method for internal caudate nucleus segmentation based on machine learning. Moreover, the ratio between right caudate body volume and the bilateral caudate body volume is applied in a ADHD diagnostic test. We separately validate the automatic internal segmentation of caudate in head and body structures and the diagnostic test using real data from ADHD and control subjects. As a result, we show accurate internal caudate segmentation and similar performance among the proposed automatic diagnostic test and the manual annotation.
	Address	Aveiro, Portugal
	Corporate Author				Thesis
	Publisher		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	978-3-642-31297-7	Medium
	Area		Expedition		Conference	ICIAR
	Notes	OR; HuPBA; MILAB			Approved	no
	Call Number	Admin @ si @ ISG2012			Serial	2059
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	Author	David Masip; Alexander Todorov; Jordi Vitria
	Title	The Role of Facial Regions in Evaluating Social Dime			Type	Conference Article
	Year	2012	Publication	12th European Conference on Computer Vision – Workshops and Demonstrations	Abbreviated Journal
	Volume	7584	Issue	II	Pages	210-219
	Keywords	Workshops and Demonstrations
	Abstract	Facial trait judgments are an important information cue for people. Recent works in the Psychology field have stated the basis of face evaluation, defining a set of traits that we evaluate from faces (e.g. dominance, trustworthiness, aggressiveness, attractiveness, threatening or intelligence among others). We rapidly infer information from others faces, usually after a short period of time (< 1000ms) we perceive a certain degree of dominance or trustworthiness of another person from the face. Although these perceptions are not necessarily accurate, they influence many important social outcomes (such as the results of the elections or the court decisions). This topic has also attracted the attention of Computer Vision scientists, and recently a computational model to automatically predict trait evaluations from faces has been proposed. These systems try to mimic the human perception by means of applying machine learning classifiers to a set of labeled data. In this paper we perform an experimental study on the specific facial features that trigger the social inferences. Using previous results from the literature, we propose to use simple similarity maps to evaluate which regions of the face influence the most the trait inferences. The correlation analysis is performed using only appearance, and the results from the experiments suggest that each trait is correlated with specific facial characteristics.
	Address	Florence, Italy
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	Andrea Fusiello, Vittorio Murino, Rita Cucchiara
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-33867-0	Medium
	Area		Expedition		Conference	ECCVW
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ MTV2012			Serial	2171
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	Author	Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu
	Title	Low-dimensional and Comprehensive Color Texture Description			Type	Journal Article
	Year	2012	Publication	Computer Vision and Image Understanding	Abbreviated Journal	CVIU
	Volume	116	Issue	I	Pages	54-67
	Keywords
	Abstract	Image retrieval can be dealt by combining standard descriptors, such as those of MPEG-7, which are deﬁned independently for each visual cue (e.g. SCD or CLD for Color, HTD for texture or EHD for edges). A common problem is to combine similarities coming from descriptors representing different concepts in different spaces. In this paper we propose a color texture description that bypasses this problem from its inherent deﬁnition. It is based on a low dimensional space with 6 perceptual axes. Texture is described in a 3D space derived from a direct implementation of the original Julesz’s Texton theory and color is described in a 3D perceptual space. This early fusion through the blob concept in these two bounded spaces avoids the problem and allows us to derive a sparse color-texture descriptor that achieves similar performance compared to MPEG-7 in image retrieval. Moreover, our descriptor presents comprehensive qualities since it can also be applied either in segmentation or browsing: (a) a dense image representation is deﬁned from the descriptor showing a reasonable performance in locating texture patterns included in complex images; and (b) a vocabulary of basic terms is derived to build an intermediate level descriptor in natural language improving browsing by bridging semantic gap
	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	1077-3142	ISBN		Medium
	Area		Expedition		Conference
	Notes	CAT;CIC			Approved	no
	Call Number	Admin @ si @ ASV2012			Serial	1827
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	Author	Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate
	Title	Error Analysis for Lucas-Kanade Based Schemes			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7324	Issue	I	Pages	184-191
	Keywords	Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance
	Abstract	Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures.
	Address	Aveiro, Portugal
	Corporate Author				Thesis
	Publisher	Springer-Verlag Berlin Heidelberg	Place of Publication		Editor
	Language	english	Summary Language		Original Title
	Series Editor	Campilho, Aurélio and Kamel, Mohamed	Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-31294-6	Medium
	Area		Expedition		Conference	ICIAR
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ MGH2012a			Serial	1899
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	Author	Fernando Barrera; Felipe Lumbreras; Angel Sappa
	Title	Evaluation of Similarity Functions in Multimodal Stereo			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7324	Issue	I	Pages	320-329
	Keywords	Aveiro, Portugal
	Abstract	This paper presents an evaluation framework for multimodal stereo matching, which allows to compare the performance of four similarity functions. Additionally, it presents details of a multimodal stereo head that supply thermal infrared and color images, as well as, aspects of its calibration and rectification. The pipeline includes a novel method for the disparity selection, which is suitable for evaluating the similarity functions. Finally, a benchmark for comparing different initializations of the proposed framework is presented. Similarity functions are based on mutual information, gradient orientation and scale space representations. Their evaluation is performed using two metrics: i) disparity error, and ii) number of correct matches on planar regions. In addition to the proposed evaluation, the current paper also shows that 3D sparse representations can be recovered from such a multimodal stereo head.
	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	978-3-642-31294-6	Medium
	Area		Expedition		Conference	ICIAR
	Notes	ADAS			Approved	no
	Call Number	BLS2012a			Serial	2014
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	Author	Miguel Oliveira; Angel Sappa; V. Santos
	Title	Color Correction using 3D Gaussian Mixture Models			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7324	Issue	I	Pages	97-106
	Keywords
	Abstract	The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.
	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	10.1007/978-3-642-31295-3_12	Medium
	Area		Expedition		Conference	ICIAR
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ OSS2012a			Serial	2015
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	Author	R. Valenti; Theo Gevers
	Title	Accurate Eye Center Location through Invariant Isocentric Patterns			Type	Journal Article
	Year	2012	Publication	IEEE Transaction on Pattern Analysis and Machine Intelligence	Abbreviated Journal	TPAMI
	Volume	34	Issue	9	Pages	1785-1798
	Keywords
	Abstract	Impact factor 2010: 5.308 Impact factor 2011/12?: 5.96 Locating the center of the eyes allows for valuable information to be captured and used in a wide range of applications. Accurate eye center location can be determined using commercial eye-gaze trackers, but additional constraints and expensive hardware make these existing solutions unattractive and impossible to use on standard (i.e., visible wavelength), low-resolution images of eyes. Systems based solely on appearance are proposed in the literature, but their accuracy does not allow us to accurately locate and distinguish eye centers movements in these low-resolution settings. Our aim is to bridge this gap by locating the center of the eye within the area of the pupil on low-resolution images taken from a webcam or a similar device. The proposed method makes use of isophote properties to gain invariance to linear lighting changes (contrast and brightness), to achieve in-plane rotational invariance, and to keep low-computational costs. To further gain scale invariance, the approach is applied to a scale space pyramid. In this paper, we extensively test our approach for its robustness to changes in illumination, head pose, scale, occlusion, and eye rotation. We demonstrate that our system can achieve a significant improvement in accuracy over state-of-the-art techniques for eye center location in standard low-resolution imagery.
	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	0162-8828	ISBN		Medium
	Area		Expedition		Conference
	Notes	ALTRES;ISE			Approved	no
	Call Number	Admin @ si @ VaG 2012a			Serial	1849
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	Author	Jon Almazan; Alicia Fornes; Ernest Valveny
	Title	A non-rigid appearance model for shape description and recognition			Type	Journal Article
	Year	2012	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	45	Issue	9	Pages	3105--3113
	Keywords	Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition
	Abstract	In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM 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	0031-3203	ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ AFV2012			Serial	1982
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	Author	Jaume Gibert; Ernest Valveny; Horst Bunke
	Title	Graph Embedding in Vector Spaces by Node Attribute Statistics			Type	Journal Article
	Year	2012	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	45	Issue	9	Pages	3072-3083
	Keywords	Structural pattern recognition; Graph embedding; Data clustering; Graph classification
	Abstract	Graph-based representations are of broad use and applicability in pattern recognition. They exhibit, however, a major drawback with regards to the processing tools that are available in their domain. Graphembedding into vectorspaces is a growing field among the structural pattern recognition community which aims at providing a feature vector representation for every graph, and thus enables classical statistical learning machinery to be used on graph-based input patterns. In this work, we propose a novel embedding methodology for graphs with continuous nodeattributes and unattributed edges. The approach presented in this paper is based on statistics of the node labels and the edges between them, based on their similarity to a set of representatives. We specifically deal with an important issue of this methodology, namely, the selection of a suitable set of representatives. In an experimental evaluation, we empirically show the advantages of this novel approach in the context of different classification problems using several databases of graphs.
	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	0031-3203	ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ GVB2012a			Serial	1992
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	Author	Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	Towards Automatic Polyp Detection with a Polyp Appearance Model			Type	Journal Article
	Year	2012	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	45	Issue	9	Pages	3166-3182
	Keywords	Colonoscopy,PolypDetection,RegionSegmentation,SA-DOVA descriptot
	Abstract	This work aims at the automatic polyp detection by using a model of polyp appearance in the context of the analysis of colonoscopy videos. Our method consists of three stages: region segmentation, region description and region classification. The performance of our region segmentation method guarantees that if a polyp is present in the image, it will be exclusively and totally contained in a single region. The output of the algorithm also defines which regions can be considered as non-informative. We define as our region descriptor the novel Sector Accumulation-Depth of Valleys Accumulation (SA-DOVA), which provides a necessary but not sufficient condition for the polyp presence. Finally, we classify our segmented regions according to the maximal values of the SA-DOVA descriptor. Our preliminary classification results are promising, especially when classifying those parts of the image that do not contain a polyp inside.
	Address
	Corporate Author				Thesis
	Publisher	Elsevier	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0031-3203	ISBN		Medium
	Area	800	Expedition		Conference	IbPRIA
	Notes	MV;SIAI			Approved	no
	Call Number	Admin @ si @ BSV2012; IAM @ iam			Serial	1997
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	Author	Mario Hernandez; Joao Sanchez; Jordi Vitria
	Title	Selected papers from Iberian Conference on Pattern Recognition and Image Analysis			Type	Book Whole
	Year	2012	Publication	Pattern Recognition	Abbreviated Journal
	Volume	45	Issue	9	Pages	3047-3582
	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	0031-3203	ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ HSV2012			Serial	2069
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