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Oriol Rodriguez-Leor; A. Carol; H. Tizon; Eduard Fernandez-Nofrerias; J. Mauri; Vicente del Valle; Debora Gil; Aura Hernandez-Sabate; Petia Radeva |
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Title |
Model estadístic-determinístic per la segmentació de l adventicia en imatges d ecografía intracoronaria |
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Journal Article |
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2005 |
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Rev Societat Catalana Cardiologia |
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5 |
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41 |
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IAM;MILAB |
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IAM @ iam @ RCT2005 |
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1637 |
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Oriol Rodriguez-Leor; Debora Gil; Eduard Fernandez-Nofrerias |
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Title |
Analisis en los cambios en el nivel de gris en las secuencias angiograficas mediante descriptores estadisticos para determinar la perfusion miocardica |
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Journal Article |
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2006 |
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Revista Española de Cardiología |
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REC |
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59 Supl 2-166 |
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2 |
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128 |
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IAM; |
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IAM @ iam @ RGF2006 |
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1640 |
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Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; C. Garcia; R. Villuendas; Vicente del Valle; Debora Gil; Petia Radeva |
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Title |
Reconstruction of a spatio-temporal model of the intima layer from intravascular ultrasound sequences |
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2003 |
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European Heart Journal |
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ESC Congress |
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IAM;MILAB |
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IAM @ iam @ RMF2003c |
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1641 |
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Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; Antonio Tovar; Vicente del Valle; Aura Hernandez-Sabate; Debora Gil; Petia Radeva |
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Title |
Utilización de la Estructura de los Campos Vectoriales para la Detección de la Adventicia en Imágenes de Ecografía Intracoronaria |
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Journal Article |
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2004 |
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Revista Internacional de Enfermedades Cardiovasculares Revista Española de Cardiología |
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57 |
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2 |
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100 |
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SEC |
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IAM;MILAB |
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no |
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IAM @ iam @ RMF2004 |
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1642 |
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Author |
Misael Rosales; Petia Radeva; Oriol Rodriguez-Leor; Debora Gil |
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Title |
Modelling of image-catheter motion for 3-D IVUS |
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Journal Article |
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Year |
2009 |
Publication |
Medical image analysis |
Abbreviated Journal |
MIA |
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13 |
Issue |
1 |
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91-104 |
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Intravascular ultrasound (IVUS); Motion estimation; Motion decomposition; Fourier |
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Abstract |
Three-dimensional intravascular ultrasound (IVUS) allows to visualize and obtain volumetric measurements of coronary lesions through an exploration of the cross sections and longitudinal views of arteries. However, the visualization and subsequent morpho-geometric measurements in IVUS longitudinal cuts are subject to distortion caused by periodic image/vessel motion around the IVUS catheter. Usually, to overcome the image motion artifact ECG-gating and image-gated approaches are proposed, leading to slowing the pullback acquisition or disregarding part of IVUS data. In this paper, we argue that the image motion is due to 3-D vessel geometry as well as cardiac dynamics, and propose a dynamic model based on the tracking of an elliptical vessel approximation to recover the rigid transformation and align IVUS images without loosing any IVUS data. We report an extensive validation with synthetic simulated data and in vivo IVUS sequences of 30 patients achieving an average reduction of the image artifact of 97% in synthetic data and 79% in real-data. Our study shows that IVUS alignment improves longitudinal analysis of the IVUS data and is a necessary step towards accurate reconstruction and volumetric measurements of 3-D IVUS. |
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IAM;MILAB |
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IAM @ iam @ RRR2009 |
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1646 |
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Author |
David Rotger; Misael Rosales; Jaume Garcia; Oriol Pujol ; J. Mauri; Petia Radeva |
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Title |
Active Vessel: A New Multimedia Workstation for Intravascular Ultrasound and Angiography Fusion |
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Journal Article |
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Year |
2003 |
Publication |
Computers in Cardiology |
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Volume |
30 |
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65-68 |
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AcriveVessel is a new multimedia workstation which enables the visualization, acquisition and handling of both image modalities, on- and ofline. It enables DICOM v3.0 decompression and browsing, video acquisition,repmduction and storage for IntraVascular UltraSound (IVUS) and angiograms with their corresponding ECG,automatic catheter segmentation in angiography images (using fast marching algorithm). BSpline models definition for vessel layers on IVUS images sequence and an extensively validated tool to fuse information. This approach defines the correspondence of every IVUS image with its correspondent point in the angiogram and viceversa. The 3 0 reconstruction of the NUS catheterhessel enables real distance measurements as well as threedimensional visualization showing vessel tortuosity in the space. |
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IAM;MILAB;HuPBA |
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no |
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IAM @ iam @ RRG2003 |
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1647 |
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Author |
Ernest Valveny; Enric Marti |
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Title |
A model for image generation and symbol recognition through the deformation of lineal shapes |
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Journal Article |
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Year |
2003 |
Publication |
Pattern Recognition Letters |
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PRL |
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24 |
Issue |
15 |
Pages |
2857-2867 |
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We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents. |
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Elsevier Science Inc. |
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New York, NY, USA |
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0167-8655 |
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DAG; IAM |
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no |
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IAM @ iam @ VAM2003 |
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1653 |
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Author |
Ernest Valveny; Enric Marti |
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Title |
Deformable Template Matching within a Bayesian Framework for Hand-Written Graphic Symbol Recognition |
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Journal Article |
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2000 |
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Graphics Recognition Recent Advances |
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1941 |
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193-208 |
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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. |
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Springer Verlag |
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Springer Verlag |
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DAG;IAM; |
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IAM @ iam @ MVA2000 |
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1655 |
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Author |
Lluis Pere de las Heras; Ahmed Sheraz; Marcus Liwicki; Ernest Valveny; Gemma Sanchez |
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Title |
Statistical Segmentation and Structural Recognition for Floor Plan Interpretation |
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Journal Article |
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2014 |
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International Journal on Document Analysis and Recognition |
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IJDAR |
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17 |
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3 |
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221-237 |
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A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents. |
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Springer Berlin Heidelberg |
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1433-2833 |
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DAG; ADAS; 600.076; 600.077 |
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HSL2014 |
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2370 |
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Author |
Jasper Uilings; Koen E.A. van de Sande; Theo Gevers; Arnold Smeulders |
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Title |
Selective Search for Object Recognition |
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Journal Article |
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Year |
2013 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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104 |
Issue |
2 |
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154-171 |
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This paper addresses the problem of generating possible object locations for use in object recognition. We introduce selective search which combines the strength of both an exhaustive search and segmentation. Like segmentation, we use the image structure to guide our sampling process. Like exhaustive search, we aim to capture all possible object locations. Instead of a single technique to generate possible object locations, we diversify our search and use a variety of complementary image partitionings to deal with as many image conditions as possible. Our selective search results in a small set of data-driven, class-independent, high quality locations, yielding 99 % recall and a Mean Average Best Overlap of 0.879 at 10,097 locations. The reduced number of locations compared to an exhaustive search enables the use of stronger machine learning techniques and stronger appearance models for object recognition. In this paper we show that our selective search enables the use of the powerful Bag-of-Words model for recognition. The selective search software is made publicly available (Software: http://disi.unitn.it/~uijlings/SelectiveSearch.html). |
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0920-5691 |
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ALTRES;ISE |
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Admin @ si @ USG2013 |
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2362 |
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Author |
Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez |
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Title |
Video Alignment for Change Detection |
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Journal Article |
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Year |
2011 |
Publication |
IEEE Transactions on Image Processing |
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TIP |
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20 |
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7 |
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1858-1869 |
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video alignment |
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In this work, we address the problem of aligning two video sequences. Such alignment refers to synchronization, i.e., the establishment of temporal correspondence between frames of the first and second video, followed by spatial registration of all the temporally corresponding frames. Video synchronization and alignment have been attempted before, but most often in the relatively simple cases of fixed or rigidly attached cameras and simultaneous acquisition. In addition, restrictive assumptions have been applied, including linear time correspondence or the knowledge of the complete trajectories of corresponding scene points; to some extent, these assumptions limit the practical applicability of any solutions developed. We intend to solve the more general problem of aligning video sequences recorded by independently moving cameras that follow similar trajectories, based only on the fusion of image intensity and GPS information. The novelty of our approach is to pose the synchronization as a MAP inference problem on a Bayesian network including the observations from these two sensor types, which have been proved complementary. Alignment results are presented in the context of videos recorded from vehicles driving along the same track at different times, for different road types. In addition, we explore two applications of the proposed video alignment method, both based on change detection between aligned videos. One is the detection of vehicles, which could be of use in ADAS. The other is online difference spotting videos of surveillance rounds. |
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ADAS; IF |
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DPS 2011; ADAS @ adas @ dps2011 |
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1705 |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Personalization and User Verification in Wearable Systems using Biometric Walking Patterns |
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Journal Article |
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2012 |
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Personal and Ubiquitous Computing |
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PUC |
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16 |
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5 |
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563-580 |
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In this article, a novel technique for user’s authentication and verification using gait as a biometric unobtrusive pattern is proposed. The method is based on a two stages pipeline. First, a general activity recognition classifier is personalized for an specific user using a small sample of her/his walking pattern. As a result, the system is much more selective with respect to the new walking pattern. A second stage verifies whether the user is an authorized one or not. This stage is defined as a one-class classification problem. In order to solve this problem, a four-layer architecture is built around the geometric concept of convex hull. This architecture allows to improve robustness to outliers, modeling non-convex shapes, and to take into account temporal coherence information. Two different scenarios are proposed as validation with two different wearable systems. First, a custom high-performance wearable system is built and used in a free environment. A second dataset is acquired from an Android-based commercial device in a ‘wild’ scenario with rough terrains, adversarial conditions, crowded places and obstacles. Results on both systems and datasets are very promising, reducing the verification error rates by an order of magnitude with respect to the state-of-the-art technologies. |
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Springer-Verlag |
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1617-4909 |
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MILAB;HuPBA |
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Admin @ si @ CPR2012 |
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1706 |
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Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Xavier Roca |
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Title |
Efficient Discriminative Multiresolution Cascade for Real-Time Human Detection Applications |
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Journal Article |
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2011 |
Publication |
Pattern Recognition Letters |
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PRL |
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32 |
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13 |
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1581-1587 |
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Human detection is fundamental in many machine vision applications, like video surveillance, driving assistance, action recognition and scene understanding. However in most of these applications real-time performance is necessary and this is not achieved yet by current detection methods.
This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a linear Support Vector Machine (SVM) composed of HOG features at different resolutions, from coarse at the first level to fine at the last one.
In contrast to previous methods, our approach uses a non-uniform stride of the sliding window that is defined by the feature resolution and allows the detection to be incrementally refined as going from coarse-to-fine resolution. In this way, the speed-up of the cascade is not only due to the fewer number of features computed at the first levels of the cascade, but also to the reduced number of windows that need to be evaluated at the coarse resolution. Experimental results show that our method reaches a detection rate comparable with the state-of-the-art of detectors based on HOG features, while at the same time the detection search is up to 23 times faster. |
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ISE |
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Admin @ si @ PGB2011a |
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1707 |
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Author |
Palaiahnakote Shivakumara; Anjan Dutta; Trung Quy Phan; Chew Lim Tan; Umapada Pal |
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Title |
A Novel Mutual Nearest Neighbor based Symmetry for Text Frame Classification in Video |
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Journal Article |
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2011 |
Publication |
Pattern Recognition |
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PR |
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In the field of multimedia retrieval in video, text frame classification is essential for text detection, event detection, event boundary detection, etc. We propose a new text frame classification method that introduces a combination of wavelet and median moment with k-means clustering to select probable text blocks among 16 equally sized blocks of a video frame. The same feature combination is used with a new Max–Min clustering at the pixel level to choose probable dominant text pixels in the selected probable text blocks. For the probable text pixels, a so-called mutual nearest neighbor based symmetry is explored with a four-quadrant formation centered at the centroid of the probable dominant text pixels to know whether a block is a true text block or not. If a frame produces at least one true text block then it is considered as a text frame otherwise it is a non-text frame. Experimental results on different text and non-text datasets including two public datasets and our own created data show that the proposed method gives promising results in terms of recall and precision at the block and frame levels. Further, we also show how existing text detection methods tend to misclassify non-text frames as text frames in term of recall and precision at both the block and frame levels. |
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Admin @ si @ SDP2011 |
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1727 |
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Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Rank Estimation in Missing Data Matrix Problems |
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Journal Article |
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2011 |
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Journal of Mathematical Imaging and Vision |
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JMIV |
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39 |
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2 |
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140-160 |
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A novel technique for missing data matrix rank estimation is presented. It is focused on matrices of trajectories, where every element of the matrix corresponds to an image coordinate from a feature point of a rigid moving object at a given frame; missing data are represented as empty entries. The objective of the proposed approach is to estimate the rank of a missing data matrix in order to fill in empty entries with some matrix completion method, without using or assuming neither the number of objects contained in the scene nor the kind of their motion. The key point of the proposed technique consists in studying the frequency behaviour of the individual trajectories, which are seen as 1D signals. The main assumption is that due to the rigidity of the moving objects, the frequency content of the trajectories will be similar after filling in their missing entries. The proposed rank estimation approach can be used in different computer vision problems, where the rank of a missing data matrix needs to be estimated. Experimental results with synthetic and real data are provided in order to empirically show the good performance of the proposed approach. |
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0924-9907 |
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Admin @ si @ JSL2011; |
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1710 |
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