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	Author	Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard
	Title	A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video			Type	Conference Article
	Year	2010	Publication	20th International Conference on Pattern Recognition	Abbreviated Journal
	Volume	6388	Issue		Pages	93–98
	Keywords
	Abstract	We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR.
	Address
	Corporate Author				Thesis
	Publisher	Springer, 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	978-3-642-17710-1	Medium
	Area		Expedition		Conference	ICPR
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ LLR2010			Serial	1459
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	Author	Debora Gil; Petia Radeva
	Title	Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling			Type	Book Chapter
	Year	2003	Publication	Energy Minimization Methods In Computer Vision And Pattern Recognition	Abbreviated Journal	LNCS
	Volume	2683	Issue		Pages	357-372
	Keywords	Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature
	Abstract	Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time.
	Address
	Corporate Author				Thesis
	Publisher	Springer, Berlin	Place of Publication	Lisbon, PORTUGAL	Editor	Springer, B.
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	3-540-40498-8	Medium
	Area		Expedition		Conference
	Notes	IAM;MILAB			Approved	no
	Call Number	IAM @ iam @ GIR2003b			Serial	1535
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	Author	Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados
	Title	Textual Descriptions for Browsing People by Visual Apperance.			Type	Book Chapter
	Year	2002	Publication	Lecture Notes in Artificial Intelligence	Abbreviated Journal
	Volume	2504	Issue		Pages	419-429
	Keywords
	Abstract	This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building
	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		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG;CIC			Approved	no
	Call Number	CAT @ cat @ TBB2002b			Serial	319
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	Author	Fernando Vilariño; Petia Radeva
	Title	Patch-Optimized Discriminant Active Contours for Medical Image Segmentation.			Type	Conference Article
	Year	2002	Publication	Iberoamerican Conference on Artificial Intelligence	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Sevilla, Espanya
	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		ISBN		Medium
	Area		Expedition		Conference	IBERAMIA
	Notes	MV;MILAB;SIAI			Approved	no
	Call Number	BCNPCL @ bcnpcl @ ViR2002; IAM @ iam @ VRa2003			Serial	320
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	Author	Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva
	Title	Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions			Type	Book Chapter
	Year	2006	Publication	9th International Conference on Medical Image Computing and Computer–Assisted Intervention	Abbreviated Journal
	Volume	4191	Issue		Pages	161–168
	Keywords
	Abstract	Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of con- tractions and to analyze the intestine motility. Feature extraction is es- sential for getting efficient patterns to detect contractions in wireless video endoscopy of small intestine. We propose a novel method based on anisotropic image filtering and efficient statistical classification of con- traction features. In particular, we apply the image gradient tensor for mining informative skeletons from the original image and a sequence of descriptors for capturing the characteristic pattern of contractions. Fea- tures extracted from the endoluminal images were evaluated in terms of their discriminatory ability in correct classifying images as either belong- ing to contractions or not. Classification was performed by means of a support vector machine classifier with a radial basis function kernel. Our classification rates gave sensitivity of the order of 90.84% and specificity of the order of 94.43% respectively. These preliminary results highlight the high efficiency of the selected descriptors and support the feasibility of the proposed method in assisting the automatic detection and analysis of contractions.
	Address	Copenhagen (Denmark)
	Corporate Author				Thesis
	Publisher	Springer Verlag	Place of Publication	Berlin Heidelberg	Editor	R. Larsen, M. Nielsen, and J. Sporring
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference	MICCAI06
	Notes	MV;OR;MILAB;SIAI			Approved	no
	Call Number	BCNPCL @ bcnpcl @ SVV2006; IAM @ iam @ SVV2006			Serial	725
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	Author	Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; C. Malagelada; Petia Radeva
	Title	Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions			Type	Book Chapter
	Year	2006	Publication	11th Iberoamerican Congress on Pattern Recognition	Abbreviated Journal
	Volume	4225	Issue		Pages	178–187
	Keywords
	Abstract	This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns.
	Address	Cancun (Mexico)
	Corporate Author				Thesis
	Publisher	Springer Verlag	Place of Publication	Berlin Heidelberg	Editor	.F. Mart ́ınez-Trinidad et al
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference
	Notes	MV;OR;MILAB;SIAI			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f			Serial	728
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	Author	Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; C. Malagelada; Petia Radeva
	Title	A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment			Type	Book Chapter
	Year	2006	Publication	11th Iberoamerican Congress on Pattern Recognition	Abbreviated Journal
	Volume	4225	Issue		Pages	188–197
	Keywords
	Abstract	Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment.
	Address	Cancun (Mexico)
	Corporate Author				Thesis
	Publisher	Springer Verlag	Place of Publication	Berlin-Heidelberg	Editor	J.P. Martinez–Trinidad et al
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference	CIARP06
	Notes	MV;OR;MILAB;SIAI			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e			Serial	729
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	Author	Fadi Dornaika; Angel Sappa
	Title	Improving Appearance-Based 3D Face Tracking Using Sparse Stereo Data			Type	Conference Article
	Year	2007	Publication	Advances in Computer Graphics and Computer Vision,	Abbreviated Journal
	Volume		Issue		Pages	354–366
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	Springer Verlag	Place of Publication		Editor	J. Braz, A. Ranchordas, H. Araujo and J. Jorge,
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	VISAPP
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ DoS2007d			Serial	1046
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	Author	Wenjuan Gong; Andrew Bagdanov; Xavier Roca; Jordi Gonzalez
	Title	Automatic Key Pose Selection for 3D Human Action Recognition			Type	Conference Article
	Year	2010	Publication	6th International Conference on Articulated Motion and Deformable Objects	Abbreviated Journal
	Volume	6169	Issue		Pages	290–299
	Keywords
	Abstract	This article describes a novel approach to the modeling of human actions in 3D. The method we propose is based on a “bag of poses” model that represents human actions as histograms of key-pose occurrences over the course of a video sequence. Actions are first represented as 3D poses using a sequence of 36 direction cosines corresponding to the angles 12 joints form with the world coordinate frame in an articulated human body model. These pose representations are then projected to three-dimensional, action-specific principal eigenspaces which we refer to as aSpaces. We introduce a method for key-pose selection based on a local-motion energy optimization criterion and we show that this method is more stable and more resistant to noisy data than other key-poses selection criteria for action recognition.
	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	0302-9743	ISBN	978-3-642-14060-0	Medium
	Area		Expedition		Conference	AMDO
	Notes	ISE			Approved	no
	Call Number	DAG @ dag @ GBR2010			Serial	1317
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	Author	Ernest Valveny; Enric Marti
	Title	Deformable Template Matching within a Bayesian Framework for Hand-Written Graphic Symbol Recognition			Type	Journal Article
	Year	2000	Publication	Graphics Recognition Recent Advances	Abbreviated Journal
	Volume	1941	Issue		Pages	193-208
	Keywords
	Abstract	We describe a method for hand-drawn symbol recognition based on deformable template matching able to handle uncertainty and imprecision inherent to hand-drawing. Symbols are represented as a set of straight lines and their deformations as geometric transformations of these lines. Matching, however, is done over the original binary image to avoid loss of information during line detection. It is defined as an energy minimization problem, using a Bayesian framework which allows to combine fidelity to ideal shape of the symbol and flexibility to modify the symbol in order to get the best fit to the binary input image. Prior to matching, we find the best global transformation of the symbol to start the recognition process, based on the distance between symbol lines and image lines. We have applied this method to the recognition of dimensions and symbols in architectural floor plans and we show its flexibility to recognize distorted symbols.
	Address
	Corporate Author	Springer Verlag			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		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG;IAM;			Approved	no
	Call Number	IAM @ iam @ MVA2000			Serial	1655
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	Author	Jose Manuel Alvarez; Theo Gevers; Antonio Lopez
	Title	Learning photometric invariance for object detection			Type	Journal Article
	Year	2010	Publication	International Journal of Computer Vision	Abbreviated Journal	IJCV
	Volume	90	Issue	1	Pages	45-61
	Keywords	road detection
	Abstract	Impact factor: 3.508 (the last available from JCR2009SCI). Position 4/103 in the category Computer Science, Artificial Intelligence. Quartile Color is a powerful visual cue in many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the imaging conditions that negatively affect the performance of the task at hand. Often, a reflection model (e.g., Lambertian or dichromatic reflectance) is used to derive color invariant models. However, this approach may be too restricted to model real-world scenes in which different reflectance mechanisms can hold simultaneously. Therefore, in this paper, we aim to derive color invariance by learning from color models to obtain diversified color invariant ensembles. First, a photometrical orthogonal and non-redundant color model set is computed composed of both color variants and invariants. Then, the proposed method combines these color models to arrive at a diversified color ensemble yielding a proper balance between invariance (repeatability) and discriminative power (distinctiveness). To achieve this, our fusion method uses a multi-view approach to minimize the estimation error. In this way, the proposed method is robust to data uncertainty and produces properly diversified color invariant ensembles. Further, the proposed method is extended to deal with temporal data by predicting the evolution of observations over time. Experiments are conducted on three different image datasets to validate the proposed method. Both the theoretical and experimental results show that the method is robust against severe variations in imaging conditions. The method is not restricted to a certain reflection model or parameter tuning, and outperforms state-of-the-art detection techniques in the field of object, skin and road recognition. Considering sequential data, the proposed method (extended to deal with future observations) outperforms the other methods
	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	ADAS;ISE			Approved	no
	Call Number	ADAS @ adas @ AGL2010c			Serial	1451
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	Author	Palaiahnakote Shivakumara; Anjan Dutta; Chew Lim Tan; Umapada Pal
	Title	Multi-oriented scene text detection in video based on wavelet and angle projection boundary growing			Type	Journal Article
	Year	2014	Publication	Multimedia Tools and Applications	Abbreviated Journal	MTAP
	Volume	72	Issue	1	Pages	515-539
	Keywords
	Abstract	In this paper, we address two complex issues: 1) Text frame classification and 2) Multi-oriented text detection in video text frame. We first divide a video frame into 16 blocks and propose a combination of wavelet and median-moments with k-means clustering at the block level to identify probable text blocks. For each probable text block, the method applies the same combination of feature with k-means clustering over a sliding window running through the blocks to identify potential text candidates. We introduce a new idea of symmetry on text candidates in each block based on the observation that pixel distribution in text exhibits a symmetric pattern. The method integrates all blocks containing text candidates in the frame and then all text candidates are mapped on to a Sobel edge map of the original frame to obtain text representatives. To tackle the multi-orientation problem, we present a new method called Angle Projection Boundary Growing (APBG) which is an iterative algorithm and works based on a nearest neighbor concept. APBG is then applied on the text representatives to fix the bounding box for multi-oriented text lines in the video frame. Directional information is used to eliminate false positives. Experimental results on a variety of datasets such as non-horizontal, horizontal, publicly available data (Hua’s data) and ICDAR-03 competition data (camera images) show that the proposed method outperforms existing methods proposed for video and the state of the art methods for scene text as well.
	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	1380-7501	ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ SDT2014			Serial	2357
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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	Cesar Isaza; Joaquin Salas; Bogdan Raducanu
	Title	Rendering ground truth data sets to detect shadows cast by static objects in outdoors			Type	Journal Article
	Year	2014	Publication	Multimedia Tools and Applications	Abbreviated Journal	MTAP
	Volume	70	Issue	1	Pages	557-571
	Keywords	Synthetic ground truth data set; Sun position; Shadow detection; Static objects shadow detection
	Abstract	In our work, we are particularly interested in studying the shadows cast by static objects in outdoor environments, during daytime. To assess the accuracy of a shadow detection algorithm, we need ground truth information. The collection of such information is a very tedious task because it is a process that requires manual annotation. To overcome this severe limitation, we propose in this paper a methodology to automatically render ground truth using a virtual environment. To increase the degree of realism and usefulness of the simulated environment, we incorporate in the scenario the precise longitude, latitude and elevation of the actual location of the object, as well as the sun’s position for a given time and day. To evaluate our method, we consider a qualitative and a quantitative comparison. In the quantitative one, we analyze the shadow cast by a real object in a particular geographical location and its corresponding rendered model. To evaluate qualitatively the methodology, we use some ground truth images obtained both manually and automatically.
	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	1380-7501	ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ ISR2014			Serial	2229
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