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| Author | David Vazquez; Jiaolong Xu; Sebastian Ramos; Antonio Lopez; Daniel Ponsa | ||||
Title  |
Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes | Type | Conference Article | ||
| Year | 2013 | Publication | CVPR Workshop on Ground Truth – What is a good dataset? | Abbreviated Journal | |
| Volume | Issue | Pages | 706 - 711 | ||
| Keywords | Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Among the components of a pedestrian detector, its trained pedestrian classifier is crucial for achieving the desired performance. The initial task of the training process consists in collecting samples of pedestrians and background, which involves tiresome manual annotation of pedestrian bounding boxes (BBs). Thus, recent works have assessed the use of automatically collected samples from photo-realistic virtual worlds. However, learning from virtual-world samples and testing in real-world images may suffer the dataset shift problem. Accordingly, in this paper we assess an strategy to collect samples from the real world and retrain with them, thus avoiding the dataset shift, but in such a way that no BBs of real-world pedestrians have to be provided. In particular, we train a pedestrian classifier based on virtual-world samples (no human annotation required). Then, using such a classifier we collect pedestrian samples from real-world images by detection. After, a human oracle rejects the false detections efficiently (weak annotation). Finally, a new classifier is trained with the accepted detections. We show that this classifier is competitive with respect to the counterpart trained with samples collected by manually annotating hundreds of pedestrian BBs. | ||||
| Address | Portland; Oregon; June 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | IEEE | Place of Publication | Editor | ||
| Language | English | Summary Language | English | Original Title | |
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CVPRW | ||
| Notes | ADAS; 600.054; 600.057; 601.217 | Approved | no | ||
| Call Number | ADAS @ adas @ VXR2013a | Serial | 2219 | ||
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| Author | David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin | ||||
| Title |
Virtual Worlds and Active Learning for Human Detection | Type | Conference Article | ||
| Year | 2011 | Publication | 13th International Conference on Multimodal Interaction | Abbreviated Journal | |
| Volume | Issue | Pages | 393-400 | ||
| Keywords | Pedestrian Detection; Human detection; Virtual; Domain Adaptation; Active Learning | ||||
| Abstract | Image based human detection is of paramount interest due to its potential applications in fields such as advanced driving assistance, surveillance and media analysis. However, even detecting non-occluded standing humans remains a challenge of intensive research. The most promising human detectors rely on classifiers developed in the discriminative paradigm, i.e., trained with labelled samples. However, labeling is a manual intensive step, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, some authors have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of rendered images, i.e., using realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera, or similar ones. Accordingly, in this paper we address the challenge of using a virtual world for gathering (while playing a videogame) a large amount of automatically labelled samples (virtual humans and background) and then training a classifier that performs equal, in real-world images, than the one obtained by equally training from manually labelled real-world samples. For doing that, we cast the problem as one of domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we propose a non-standard active learning technique. Therefore, ultimately our human model is learnt by the combination of virtual and real world labelled samples (Fig. 1), which has not been done before. We present quantitative results showing that this approach is valid. | ||||
| Address | Alicante, Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | ACM DL | Place of Publication | New York, NY, USA, USA | Editor | |
| Language | English | Summary Language | English | Original Title | Virtual Worlds and Active Learning for Human Detection |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4503-0641-6 | Medium | ||
| Area | Expedition | Conference | ICMI | ||
| Notes | ADAS | Approved | yes | ||
| Call Number | ADAS @ adas @ VLP2011a | Serial | 1683 | ||
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| Author | Carles Sanchez | ||||
| Title |
Tracheal ring detection in bronchoscopy | Type | Report | ||
| Year | 2011 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 168 | Issue | Pages | ||
| Keywords | Bronchoscopy, tracheal ring, segmentation | ||||
| Abstract | Endoscopy is the process in which a camera is introduced inside a human.
Given that endoscopy provides realistic images (in contrast to other modalities) and allows non-invase minimal intervention procedures (which can aid in diagnosis and surgical interventions), its use has spreaded during last decades. In this project we will focus on bronchoscopic procedures, during which the camera is introduced through the trachea in order to have a diagnostic of the patient. The diagnostic interventions are focused on: degree of stenosis (reduction in tracheal area), prosthesis or early diagnosis of tumors. In the first case, assessment of the luminal area and the calculation of the diameters of the tracheal rings are required. A main limitation is that all the process is done by hand, which means that the doctor takes all the measurements and decisions just by looking at the screen. As far as we know there is no computational framework for helping the doctors in the diagnosis. This project will consist of analysing bronchoscopic videos in order to extract useful information for the diagnostic of the degree of stenosis. In particular we will focus on segmentation of the tracheal rings. As a result of this project several strategies (for detecting tracheal rings) had been implemented in order to compare their performance. |
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| Corporate Author | Thesis | Master's thesis | |||
| Publisher | Place of Publication | Editor | Debora Gil, F.Javier Sanchez | ||
| Language | english | Summary Language | english | Original Title | |
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| Area | Expedition | Conference | |||
| Notes | IAM;MV | Approved | no | ||
| Call Number | IAM @ iam @ San2011 | Serial | 1841 | ||
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| Author | Aura Hernandez-Sabate; Debora Gil | ||||
| Title |
The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries | Type | Book Chapter | ||
| Year | 2012 | Publication | Intravascular Ultrasound | Abbreviated Journal | |
| Volume | Issue | Pages | 185-206 | ||
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| Publisher | Intech | Place of Publication | Editor | Yasuhiro Honda | |
| Language | English | Summary Language | english | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-953-307-900-4 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | IAM; ADAS | Approved | no | ||
| Call Number | IAM @ iam @ HeG2012 | Serial | 1684 | ||
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| Author | David Geronimo; Frederic Lerasle; Antonio Lopez | ||||
| Title |
State-driven particle filter for multi-person tracking | Type | Conference Article | ||
| Year | 2012 | Publication | 11th International Conference on Advanced Concepts for Intelligent Vision Systems | Abbreviated Journal | |
| Volume | 7517 | Issue | Pages | 467-478 | |
| Keywords | human tracking | ||||
| Abstract | Multi-person tracking can be exploited in applications such as driver assistance, surveillance, multimedia and human-robot interaction. With the help of human detectors, particle filters offer a robust method able to filter noisy detections and provide temporal coherence. However, some traditional problems such as occlusions with other targets or the scene, temporal drifting or even the lost targets detection are rarely considered, making the systems performance decrease. Some authors propose to overcome these problems using heuristics not explained
and formalized in the papers, for instance by defining exceptions to the model updating depending on tracks overlapping. In this paper we propose to formalize these events by the use of a state-graph, defining the current state of the track (e.g., potential , tracked, occluded or lost) and the transitions between states in an explicit way. This approach has the advantage of linking track actions such as the online underlying models updating, which gives flexibility to the system. It provides an explicit representation to adapt the multiple parallel trackers depending on the context, i.e., each track can make use of a specific filtering strategy, dynamic model, number of particles, etc. depending on its state. We implement this technique in a single-camera multi-person tracker and test it in public video sequences. |
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| Address | Brno, Chzech Republic | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer | Place of Publication | Heidelberg | Editor | J. Blanc-Talon et al. |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ACIVS | ||
| Notes | ADAS | Approved | yes | ||
| Call Number | GLL2012; ADAS @ adas @ gll2012a | Serial | 1990 | ||
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| Author | Javier Marin; David Geronimo; David Vazquez; Antonio Lopez | ||||
| Title |
Pedestrian Detection: Exploring Virtual Worlds | Type | Book Chapter | ||
| Year | 2012 | Publication | Handbook of Pattern Recognition: Methods and Application | Abbreviated Journal | |
| Volume | 5 | Issue | Pages | 145-162 | |
| Keywords | Virtual worlds; Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Handbook of pattern recognition will include contributions from university educators and active research experts. This Handbook is intended to serve as a basic reference on methods and applications of pattern recognition. The primary aim of this handbook is providing the community of pattern recognition with a readable, easy to understand resource that covers introductory, intermediate and advanced topics with equal clarity. Therefore, the Handbook of pattern recognition can serve equally well as reference resource and as classroom textbook. Contributions cover all methods, techniques and applications of pattern recognition. A tentative list of relevant topics might include: 1- Statistical, structural, syntactic pattern recognition. 2- Neural networks, machine learning, data mining. 3- Discrete geometry, algebraic, graph-based techniques for pattern recognition. 4- Face recognition, Signal analysis, image coding and processing, shape and texture analysis. 5- Document processing, text and graphics recognition, digital libraries. 6- Speech recognition, music analysis, multimedia systems. 7- Natural language analysis, information retrieval. 8- Biometrics, biomedical pattern analysis and information systems. 9- Other scientific, engineering, social and economical applications of pattern recognition. 10- Special hardware architectures, software packages for pattern recognition. | ||||
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| Publisher | iConcept Press | Place of Publication | Editor | ||
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-477554-82-1 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ MGV2012 | Serial | 1979 | ||
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| Author | Muhammad Anwer Rao; David Vazquez; Antonio Lopez | ||||
| Title |
Opponent Colors for Human Detection | Type | Conference Article | ||
| Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 6669 | Issue | Pages | 363-370 | |
| Keywords | Pedestrian Detection; Color; Part Based Models | ||||
| Abstract | Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper. | ||||
| Address | Las Palmas de Gran Canaria. Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer | Place of Publication | Berlin Heidelberg | Editor | J. Vitria; J.M. Sanches; M. Hernandez |
| Language | English | Summary Language | English | Original Title | Opponent Colors for Human Detection |
| Series Editor | Series Title | Lecture Notes on Computer Science | Abbreviated Series Title | LNCS | |
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-21256-7 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ RVL2011a | Serial | 1666 | ||
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| Author | Ferran Poveda; Debora Gil ;Albert Andaluz ;Enric Marti | ||||
| Title |
Multiscale Tractography for Representing Heart Muscular Architecture | Type | Conference Article | ||
| Year | 2011 | Publication | In MICCAI 2011 Workshop on Computational Diffusion MRI | Abbreviated Journal | |
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| Abstract | Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. Although the muscular architecture of the heart has been debated by countless researchers, the controversy is still alive. Diffusion Tensor MRI, DT-MRI, is a unique imaging technique for computational validation of the muscular structure of the heart. By the complex arrangement of myocites, existing techniques can not provide comprehensive descriptions of the global muscular architecture. In this paper we introduce a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and indicate a global helical organization | ||||
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| Language | English | Summary Language | english | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CDRMI | ||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ PGA2011 | Serial | 1681 | ||
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| Author | Sergio Vera; Debora Gil; Antonio Lopez; Miguel Angel Gonzalez Ballester | ||||
| Title |
Multilocal Creaseness Measure | Type | Journal | ||
| Year | 2012 | Publication | The Insight Journal | Abbreviated Journal | IJ |
| Volume | Issue | Pages | |||
| Keywords | Ridges, Valley, Creaseness, Structure Tensor, Skeleton, | ||||
| Abstract | This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission. | ||||
| Address | |||||
| Corporate Author | Alma IT Systems | Thesis | |||
| Publisher | Place of Publication | Editor | |||
| Language | english | Summary Language | english | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | |||
| Notes | IAM;ADAS; | Approved | no | ||
| Call Number | IAM @ iam @ VGL2012 | Serial | 1840 | ||
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| Author | Debora Gil; Agnes Borras; Manuel Ballester; Francesc Carreras; Ruth Aris; Manuel Vazquez; Enric Marti; Ferran Poveda | ||||
| Title |
MIOCARDIA: Integrating cardiac function and muscular architecture for a better diagnosis | Type | Conference Article | ||
| Year | 2011 | Publication | 14th International Symposium on Applied Sciences in Biomedical and Communication Technologies | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. The MIOCARDIA project is a multidisciplinary project in cooperation with l'Hospital de la Santa Creu i de Sant Pau, Clinica la Creu Blanca and Barcelona Supercomputing Center. The ultimate goal of this project is defining a computational model of the myocardium. The model takes into account the deep interrelation between the anatomy and the mechanics of the heart. The paper explains the workflow of the MIOCARDIA project. It also introduces a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and provides evidences of a global helical organization. | ||||
| Address | Barcelona; Spain | ||||
| Corporate Author | Association for Computing Machinery | Thesis | |||
| Publisher | Place of Publication | Barcelona, Spain | Editor | Association for Computing Machinery | |
| Language | english | Summary Language | english | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4503-0913-4 | Medium | ||
| Area | Expedition | Conference | ISABEL | ||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ GGB2011 | Serial | 1691 | ||
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| Author | Javier Marin; David Vazquez; David Geronimo; Antonio Lopez | ||||
| Title |
Learning Appearance in Virtual Scenarios for Pedestrian Detection | Type | Conference Article | ||
| Year | 2010 | Publication | 23rd IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 137–144 | ||
| Keywords | Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Detecting pedestrians in images is a key functionality to avoid vehicle-to-pedestrian collisions. The most promising detectors rely on appearance-based pedestrian classifiers trained with labelled samples. This paper addresses the following question: can a pedestrian appearance model learnt in virtual scenarios work successfully for pedestrian detection in real images? (Fig. 1). Our experiments suggest a positive answer, which is a new and relevant conclusion for research in pedestrian detection. More specifically, we record training sequences in virtual scenarios and then appearance-based pedestrian classifiers are learnt using HOG and linear SVM. We test such classifiers in a publicly available dataset provided by Daimler AG for pedestrian detection benchmarking. This dataset contains real world images acquired from a moving car. The obtained result is compared with the one given by a classifier learnt using samples coming from real images. The comparison reveals that, although virtual samples were not specially selected, both virtual and real based training give rise to classifiers of similar performance. | ||||
| Address | San Francisco; CA; USA; June 2010 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | English | Summary Language | English | Original Title | Learning Appearance in Virtual Scenarios for Pedestrian Detection |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1063-6919 | ISBN | 978-1-4244-6984-0 | Medium | |
| Area | Expedition | Conference | CVPR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ MVG2010 | Serial | 1304 | ||
| Permanent link to this record | |||||
| Author | David Vazquez; Antonio Lopez; Daniel Ponsa; David Geronimo | ||||
| Title |
Interactive Training of Human Detectors | Type | Book Chapter | ||
| Year | 2013 | Publication | Multiodal Interaction in Image and Video Applications | Abbreviated Journal | |
| Volume | 48 | Issue | Pages | 169-182 | |
| Keywords | Pedestrian Detection; Virtual World; AdaBoost; Domain Adaptation | ||||
| Abstract | Image based human detection remains as a challenging problem. Most promising detectors rely on classifiers trained with labelled samples. However, labelling is a manual labor intensive step. To overcome this problem we propose to collect images of pedestrians from a virtual city, i.e., with automatic labels, and train a pedestrian detector with them, which works fine when such virtual-world data are similar to testing one, i.e., real-world pedestrians in urban areas. When testing data is acquired in different conditions than training one, e.g., human detection in personal photo albums, dataset shift appears. In previous work, we cast this problem as one of domain adaptation and solve it with an active learning procedure. In this work, we focus on the same problem but evaluating a different set of faster to compute features, i.e., Haar, EOH and their combination. In particular, we train a classifier with virtual-world data, using such features and Real AdaBoost as learning machine. This classifier is applied to real-world training images. Then, a human oracle interactively corrects the wrong detections, i.e., few miss detections are manually annotated and some false ones are pointed out too. A low amount of manual annotation is fixed as restriction. Real- and virtual-world difficult samples are combined within what we call cool world and we retrain the classifier with this data. Our experiments show that this adapted classifier is equivalent to the one trained with only real-world data but requiring 90% less manual annotations. | ||||
| Address | Springer Heidelberg New York Dordrecht London | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
| Area | Expedition | Conference | |||
| Notes | ADAS; 600.057; 600.054; 605.203 | Approved | no | ||
| Call Number | VLP2013; ADAS @ adas @ vlp2013 | Serial | 2193 | ||
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| Author | Yainuvis Socarras; David Vazquez; Antonio Lopez; David Geronimo; Theo Gevers | ||||
| Title |
Improving HOG with Image Segmentation: Application to Human Detection | Type | Conference Article | ||
| Year | 2012 | Publication | 11th International Conference on Advanced Concepts for Intelligent Vision Systems | Abbreviated Journal | |
| Volume | 7517 | Issue | Pages | 178-189 | |
| Keywords | Segmentation; Pedestrian Detection | ||||
| Abstract | In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement.
We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4:47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function. |
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| Address | Brno, Czech Republic | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | J. Blanc-Talon et al. | |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-33139-8 | Medium | |
| Area | Expedition | Conference | ACIVS | ||
| Notes | ADAS;ISE | Approved | no | ||
| Call Number | ADAS @ adas @ SLV2012 | Serial | 1980 | ||
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| Author | Albert Andaluz | ||||
| Title |
Harmonic Phase Flow: User's guide | Type | Manual | ||
| Year | 2012 | Publication | CVC | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | HPF is a plugin for the computation of clinical scores under Osirix.
This manual provides a basic guide for experienced clinical staff. Chapter 1 provides the theoretical background in which this plugin is based. Next, in chapter 2 we provide basic instructions for installing and uninstalling this plugin. chapter 3we shows a step-by-step scenario to compute clinical scores from tagged-MRI images with HPF. Finally, in chapter 4 we provide a quick guide for plugin developers |
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| Address | Bellaterra, Barcelona (Spain) | ||||
| Corporate Author | Computer Vision Center | Thesis | |||
| Publisher | CVC | Place of Publication | Barcelona | Editor | |
| Language | english | Summary Language | english | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
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| Area | Expedition | Conference | |||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ And2012 | Serial | 1863 | ||
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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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