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| Author | Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin-Yuste; Manel Sabate; Petia Radeva | ||||
| Title | Accurate coronary centerline extraction, caliber estimation and catheter detection in angiographies | Type  |
Journal Article | ||
| Year | 2012 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | TITB |
| Volume | 16 | Issue | 6 | Pages | 1332-1340 |
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| Abstract | Segmentation of coronary arteries in X-Ray angiography is a fundamental tool to evaluate arterial diseases and choose proper coronary treatment. The accurate segmentation of coronary arteries has become an important topic for the registration of different modalities which allows physicians rapid access to different medical imaging information from Computed Tomography (CT) scans or Magnetic Resonance Imaging (MRI). In this paper, we propose an accurate fully automatic algorithm based on Graph-cuts for vessel centerline extraction, caliber estimation, and catheter detection. Vesselness, geodesic paths, and a new multi-scale edgeness map are combined to customize the Graph-cuts approach to the segmentation of tubular structures, by means of a global optimization of the Graph-cuts energy function. Moreover, a novel supervised learning methodology that integrates local and contextual information is proposed for automatic catheter detection. We evaluate the method performance on three datasets coming from different imaging systems. The method performs as good as the expert observer w.r.t. centerline detection and caliber estimation. Moreover, the method discriminates between arteries and catheter with an accuracy of 96.5%, sensitivity of 72%, and precision of 97.4%. | ||||
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| ISSN | 1089-7771 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ HGE2012 | Serial | 2141 | ||
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| Author | Laura Igual; Joan Carles Soliva; Sergio Escalera; Roger Gimeno; Oscar Vilarroya; Petia Radeva | ||||
| Title | Automatic Brain Caudate Nuclei Segmentation and Classification in Diagnostic of Attention-Deficit/Hyperactivity Disorder | Type |
Journal Article | ||
| Year | 2012 | Publication | Computerized Medical Imaging and Graphics | Abbreviated Journal | CMIG |
| Volume | 36 | Issue | 8 | Pages | 591-600 |
| Keywords | Automatic caudate segmentation; Attention-Deficit/Hyperactivity Disorder; Diagnostic test; Machine learning; Decision stumps; Dissociated dipoles | ||||
| Abstract | We present a fully automatic diagnostic imaging test for Attention-Deficit/Hyperactivity Disorder diagnosis assistance based on previously found evidences of caudate nucleus volumetric abnormalities. The proposed method consists of different steps: a new automatic method for external and internal segmentation of caudate based on Machine Learning methodologies; the definition of a set of new volume relation features, 3D Dissociated Dipoles, used for caudate representation and classification. We separately validate the contributions using real data from a pediatric population and show precise internal caudate segmentation and discrimination power of the diagnostic test, showing significant performance improvements in comparison to other state-of-the-art methods. | ||||
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| Area | Expedition | Conference | |||
| Notes | OR; HuPBA; MILAB | Approved | no | ||
| Call Number | Admin @ si @ ISE2012 | Serial | 2143 | ||
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| Author | Laura Igual; Agata Lapedriza; Ricard Borras | ||||
| Title | Robust Gait-Based Gender Classification using Depth Cameras | Type |
Journal Article | ||
| Year | 2013 | Publication | EURASIP Journal on Advances in Signal Processing | Abbreviated Journal | EURASIPJ |
| Volume | 37 | Issue | 1 | Pages | 72-80 |
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| Abstract | This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section. | ||||
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| Notes | MILAB; OR;MV | Approved | no | ||
| Call Number | Admin @ si @ ILB2013 | Serial | 2144 | ||
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| Author | Antonio Hernandez; Miguel Reyes; Victor Ponce; Sergio Escalera | ||||
| Title | GrabCut-Based Human Segmentation in Video Sequences | Type |
Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 12 | Issue | 11 | Pages | 15376-15393 |
| Keywords | segmentation; human pose recovery; GrabCut; GraphCut; Active Appearance Models; Conditional Random Field | ||||
| Abstract | In this paper, we present a fully-automatic Spatio-Temporal GrabCut human segmentation methodology that combines tracking and segmentation. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model. Spatial information is included by Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, full face and pose recovery is obtained by combining human segmentation with Active Appearance Models and Conditional Random Fields. Results over public datasets and in a new Human Limb dataset show a robust segmentation and recovery of both face and pose using the presented methodology. | ||||
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| Area | Expedition | Conference | |||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ HRP2012 | Serial | 2147 | ||
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| Author | Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras | ||||
| Title | Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot | Type |
Journal Article | ||
| Year | 2012 | Publication | Journal of Intelligent and Robotic Systems | Abbreviated Journal | JIRC |
| Volume | 68 | Issue | 2 | Pages | 185-208 |
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| Abstract | This paper addresses visual object perception applied to mobile robotics. Being able to perceive household objects in unstructured environments is a key capability in order to make robots suitable to perform complex tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. The paper brings to attention some of the issues with applying three state of the art object recognition and detection methods in a mobile robotics scenario, and proposes methods to deal with windowing/segmentation. Thus, this work aims at evaluating the state-of-the-art in object perception in an attempt to develop a lightweight solution for mobile robotics use/research in typical indoor settings. | ||||
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| Publisher | Springer Netherlands | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0921-0296 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ RAV2012 | Serial | 2150 | ||
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| Author | Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva | ||||
| Title | Adaptable image cuts for motility inspection using WCE | Type |
Journal Article | ||
| Year | 2013 | Publication | Computerized Medical Imaging and Graphics | Abbreviated Journal | CMIG |
| Volume | 37 | Issue | 1 | Pages | 72-80 |
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| Abstract | The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE. | ||||
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| Notes | MILAB; OR; 600.046; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ DSM2012 | Serial | 2151 | ||
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| Author | Cristhian Aguilera; Fernando Barrera; Felipe Lumbreras; Angel Sappa; Ricardo Toledo | ||||
| Title | Multispectral Image Feature Points | Type |
Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 12 | Issue | 9 | Pages | 12661-12672 |
| Keywords | multispectral image descriptor; color and infrared images; feature point descriptor | ||||
| Abstract | Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art. | ||||
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ ABL2012 | Serial | 2154 | ||
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| Author | Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
| Title | Multimodal Stereo Vision System: 3D Data Extraction and Algorithm Evaluation | Type |
Journal Article | ||
| Year | 2012 | Publication | IEEE Journal of Selected Topics in Signal Processing | Abbreviated Journal | J-STSP |
| Volume | 6 | Issue | 5 | Pages | 437-446 |
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| Abstract | This paper proposes an imaging system for computing sparse depth maps from multispectral images. A special stereo head consisting of an infrared and a color camera defines the proposed multimodal acquisition system. The cameras are rigidly attached so that their image planes are parallel. Details about the calibration and image rectification procedure are provided. Sparse disparity maps are obtained by the combined use of mutual information enriched with gradient information. The proposed approach is evaluated using a Receiver Operating Characteristics curve. Furthermore, a multispectral dataset, color and infrared images, together with their corresponding ground truth disparity maps, is generated and used as a test bed. Experimental results in real outdoor scenarios are provided showing its viability and that the proposed approach is not restricted to a specific domain. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1932-4553 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ BLS2012b | Serial | 2155 | ||
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| Author | David Geronimo; Joan Serrat; Antonio Lopez; Ramon Baldrich | ||||
| Title | Traffic sign recognition for computer vision project-based learning | Type |
Journal Article | ||
| Year | 2013 | Publication | IEEE Transactions on Education | Abbreviated Journal | T-EDUC |
| Volume | 56 | Issue | 3 | Pages | 364-371 |
| Keywords | traffic signs | ||||
| Abstract | This paper presents a graduate course project on computer vision. The aim of the project is to detect and recognize traffic signs in video sequences recorded by an on-board vehicle camera. This is a demanding problem, given that traffic sign recognition is one of the most challenging problems for driving assistance systems. Equally, it is motivating for the students given that it is a real-life problem. Furthermore, it gives them the opportunity to appreciate the difficulty of real-world vision problems and to assess the extent to which this problem can be solved by modern computer vision and pattern classification techniques taught in the classroom. The learning objectives of the course are introduced, as are the constraints imposed on its design, such as the diversity of students' background and the amount of time they and their instructors dedicate to the course. The paper also describes the course contents, schedule, and how the project-based learning approach is applied. The outcomes of the course are discussed, including both the students' marks and their personal feedback. | ||||
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| ISSN | 0018-9359 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS; CIC | Approved | no | ||
| Call Number | Admin @ si @ GSL2013; ADAS @ adas @ | Serial | 2160 | ||
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| Author | Joan Serrat; Felipe Lumbreras; Antonio Lopez | ||||
| Title | Cost estimation of custom hoses from STL files and CAD drawings | Type |
Journal Article | ||
| Year | 2013 | Publication | Computers in Industry | Abbreviated Journal | COMPUTIND |
| Volume | 64 | Issue | 3 | Pages | 299-309 |
| Keywords | On-line quotation; STL format; Regression; Gaussian process | ||||
| Abstract | We present a method for the cost estimation of custom hoses from CAD models. They can come in two formats, which are easy to generate: a STL file or the image of a CAD drawing showing several orthogonal projections. The challenges in either cases are, first, to obtain from them a high level 3D description of the shape, and second, to learn a regression function for the prediction of the manufacturing time, based on geometric features of the reconstructed shape. The chosen description is the 3D line along the medial axis of the tube and the diameter of the circular sections along it. In order to extract it from STL files, we have adapted RANSAC, a robust parametric fitting algorithm. As for CAD drawing images, we propose a new technique for 3D reconstruction from data entered on any number of orthogonal projections. The regression function is a Gaussian process, which does not constrain the function to adopt any specific form and is governed by just two parameters. We assess the accuracy of the manufacturing time estimation by k-fold cross validation on 171 STL file models for which the time is provided by an expert. The results show the feasibility of the method, whereby the relative error for 80% of the testing samples is below 15%. | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Notes | ADAS; 600.057; 600.054; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ SLL2013; ADAS @ adas @ | Serial | 2161 | ||
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| Author | Simone Balocco; Carlo Gatta; Marina Alberti; Xavier Carrillo; Juan Rigla; Petia Radeva | ||||
| Title | Relation between plaque type, plaque thickness, blood shear stress and plaque stress in coronary arteries assessed by X-ray Angiography and Intravascular Ultrasound | Type |
Journal Article | ||
| Year | 2012 | Publication | Medical Physics | Abbreviated Journal | MEDPHYS |
| Volume | 39 | Issue | 12 | Pages | 7430-7445 |
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| Abstract | PMID 23231293
PURPOSE: Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries. METHODS: First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations. RESULTS: The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall. CONCLUSIONS: Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed. |
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| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @BGA2012 | Serial | 2170 | ||
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| Author | Cesar Isaza; Joaquin Salas; Bogdan Raducanu | ||||
| Title | Evaluation of Intrinsic Image Algorithms to Detect the Shadows Cast by Static Objects Outdoors | Type |
Journal Article | ||
| Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 12 | Issue | 10 | Pages | 13333-13348 |
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| Abstract | In some automatic scene analysis applications, the presence of shadows becomes a nuisance that is necessary to deal with. As a consequence, a preliminary stage in many computer vision algorithms is to attenuate their effect. In this paper, we focus our attention on the detection of shadows cast by static objects outdoors, as the scene is viewed for extended periods of time (days, weeks) from a fixed camera and considering daylight intervals where the main source of light is the sun. In this context, we report two contributions. First, we introduce the use of synthetic images for which ground truth can be generated automatically, avoiding the tedious effort of manual annotation. Secondly, we report a novel application of the intrinsic image concept to the automatic detection of shadows cast by static objects in outdoors. We make both a quantitative and a qualitative evaluation of several algorithms based on this image representation. For the quantitative evaluation, we used the synthetic data set, while for the qualitative evaluation we used both data sets. Our experimental results show that the evaluated methods can partially solve the problem of shadow detection. | ||||
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| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ ISR2012b | Serial | 2173 | ||
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| Author | Fadi Dornaika; Abdelmalik Moujahid; Bogdan Raducanu | ||||
| Title | Facial expression recognition using tracked facial actions: Classifier performance analysis | Type |
Journal Article | ||
| Year | 2013 | Publication | Engineering Applications of Artificial Intelligence | Abbreviated Journal | EAAI |
| Volume | 26 | Issue | 1 | Pages | 467-477 |
| Keywords | Visual face tracking; 3D deformable models; Facial actions; Dynamic facial expression recognition; Human–computer interaction | ||||
| Abstract | In this paper, we address the analysis and recognition of facial expressions in continuous videos. More precisely, we study classifiers performance that exploit head pose independent temporal facial action parameters. These are provided by an appearance-based 3D face tracker that simultaneously provides the 3D head pose and facial actions. The use of such tracker makes the recognition pose- and texture-independent. Two different schemes are studied. The first scheme adopts a dynamic time warping technique for recognizing expressions where training data are given by temporal signatures associated with different universal facial expressions. The second scheme models temporal signatures associated with facial actions with fixed length feature vectors (observations), and uses some machine learning algorithms in order to recognize the displayed expression. Experiments quantified the performance of different schemes. These were carried out on CMU video sequences and home-made video sequences. The results show that the use of dimension reduction techniques on the extracted time series can improve the classification performance. Moreover, these experiments show that the best recognition rate can be above 90%. | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes | OR; 600.046;MV | Approved | no | ||
| Call Number | Admin @ si @ DMR2013 | Serial | 2185 | ||
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| Author | David Roche; Debora Gil; Jesus Giraldo | ||||
| Title | Multiple active receptor conformation, agonist efficacy and maximum effect of the system: the conformation-based operational model of agonism, | Type |
Journal Article | ||
| Year | 2013 | Publication | Drug Discovery Today | Abbreviated Journal | DDT |
| Volume | 18 | Issue | 7-8 | Pages | 365-371 |
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| Abstract | The operational model of agonism assumes that the maximum effect a particular receptor system can achieve (the Em parameter) is fixed. Em estimates are above but close to the asymptotic maximum effects of endogenous agonists. The concept of Em is contradicted by superagonists and those positive allosteric modulators that significantly increase the maximum effect of endogenous agonists. An extension of the operational model is proposed that assumes that the Em parameter does not necessarily have a single value for a receptor system but has multiple values associated to multiple active receptor conformations. The model provides a mechanistic link between active receptor conformation and agonist efficacy, which can be useful for the analysis of agonist response under different receptor scenarios. | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes | IAM; 600.057; 600.054 | Approved | no | ||
| Call Number | IAM @ iam @ RGG2013a | Serial | 2190 | ||
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| Author | Mikhail Mozerov | ||||
| Title | Constrained Optical Flow Estimation as a Matching Problem | Type |
Journal Article | ||
| Year | 2013 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
| Volume | 22 | Issue | 5 | Pages | 2044-2055 |
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| Abstract | In general, discretization in the motion vector domain yields an intractable number of labels. In this paper we propose an approach that can reduce general optical flow to the constrained matching problem by pre-estimating a 2D disparity labeling map of the desired discrete motion vector function. One of the goals of the proposed paper is estimating coarse distribution of motion vectors and then utilizing this distribution as global constraints for discrete optical flow estimation. This pre-estimation is done with a simple frame-to-frame correlation technique also known as the digital symmetric-phase-only-filter (SPOF). We discover a strong correlation between the output of the SPOF and the motion vector distribution of the related optical flow. The two step matching paradigm for optical flow estimation is applied: pixel accuracy (integer flow), and subpixel accuracy estimation. The matching problem is solved by global optimization. Experiments on the Middlebury optical flow datasets confirm our intuitive assumptions about strong correlation between motion vector distribution of optical flow and maximal peaks of SPOF outputs. The overall performance of the proposed method is promising and achieves state-of-the-art results on the Middlebury benchmark. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1057-7149 | ISBN | Medium | ||
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| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ Moz2013 | Serial | 2191 | ||
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