|
Records |
Links |
|
Author |
Isabelle Guyon; Lisheng Sun Hosoya; Marc Boulle; Hugo Jair Escalante; Sergio Escalera; Zhengying Liu; Damir Jajetic; Bisakha Ray; Mehreen Saeed; Michele Sebag; Alexander R.Statnikov; Wei-Wei Tu; Evelyne Viegas |
|
|
Title |
Analysis of the AutoML Challenge Series 2015-2018. |
Type |
Book Chapter |
|
Year |
2019 |
Publication |
Automated Machine Learning |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
177-219 |
|
|
Keywords |
|
|
|
Abstract |
The ChaLearn AutoML Challenge (The authors are in alphabetical order of last name, except the first author who did most of the writing and the second author who produced most of the numerical analyses and plots.) (NIPS 2015 – ICML 2016) consisted of six rounds of a machine learning competition of progressive difficulty, subject to limited computational resources. It was followed bya one-round AutoML challenge (PAKDD 2018). The AutoML setting differs from former model selection/hyper-parameter selection challenges, such as the one we previously organized for NIPS 2006: the participants aim to develop fully automated and computationally efficient systems, capable of being trained and tested without human intervention, with code submission. This chapter analyzes the results of these competitions and provides details about the datasets, which were not revealed to the participants. The solutions of the winners are systematically benchmarked over all datasets of all rounds and compared with canonical machine learning algorithms available in scikit-learn. All materials discussed in this chapter (data and code) have been made publicly available at http://automl.chalearn.org/. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
SSCML |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
HuPBA; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ GHB2019 |
Serial |
3330 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Escalera; Markus Weimer; Mikhail Burtsev; Valentin Malykh; Varvara Logacheva; Ryan Lowe; Iulian Vlad Serban; Yoshua Bengio; Alexander Rudnicky; Alan W. Black; Shrimai Prabhumoye; Łukasz Kidzinski; Mohanty Sharada; Carmichael Ong; Jennifer Hicks; Sergey Levine; Marcel Salathe; Scott Delp; Iker Huerga; Alexander Grigorenko; Leifur Thorbergsson; Anasuya Das; Kyla Nemitz; Jenna Sandker; Stephen King; Alexander S. Ecker; Leon A. Gatys; Matthias Bethge; Jordan Boyd Graber; Shi Feng; Pedro Rodriguez; Mohit Iyyer; He He; Hal Daume III; Sean McGregor; Amir Banifatemi; Alexey Kurakin; Ian Goodfellow; Samy Bengio |
|
|
Title |
Introduction to NIPS 2017 Competition Track |
Type |
Book Chapter |
|
Year |
2018 |
Publication |
The NIPS ’17 Competition: Building Intelligent Systems |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1-23 |
|
|
Keywords |
|
|
|
Abstract |
Competitions have become a popular tool in the data science community to solve hard problems, assess the state of the art and spur new research directions. Companies like Kaggle and open source platforms like Codalab connect people with data and a data science problem to those with the skills and means to solve it. Hence, the question arises: What, if anything, could NIPS add to this rich ecosystem?
In 2017, we embarked to find out. We attracted 23 potential competitions, of which we selected five to be NIPS 2017 competitions. Our final selection features competitions advancing the state of the art in other sciences such as “Classifying Clinically Actionable Genetic Mutations” and “Learning to Run”. Others, like “The Conversational Intelligence Challenge” and “Adversarial Attacks and Defences” generated new data sets that we expect to impact the progress in their respective communities for years to come. And “Human-Computer Question Answering Competition” showed us just how far we as a field have come in ability and efficiency since the break-through performance of Watson in Jeopardy. Two additional competitions, DeepArt and AI XPRIZE Milestions, were also associated to the NIPS 2017 competition track, whose results are also presented within this chapter. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
|
Editor |
Sergio Escalera; Markus Weimer |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-319-94042-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
HUPBA; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ EWB2018 |
Serial |
3200 |
|
Permanent link to this record |
|
|
|
|
Author |
Estefania Talavera; Alexandre Cola; Nicolai Petkov; Petia Radeva |
|
|
Title |
Towards Egocentric Person Re-identification and Social Pattern Analysis. |
Type |
Book Chapter |
|
Year |
2019 |
Publication |
Frontiers in Artificial Intelligence and Applications |
Abbreviated Journal |
|
|
|
Volume |
310 |
Issue |
|
Pages |
203 - 211 |
|
|
Keywords |
|
|
|
Abstract |
CoRR abs/1905.04073
Wearable cameras capture a first-person view of the daily activities of the camera wearer, offering a visual diary of the user behaviour. Detection of the appearance of people the camera user interacts with for social interactions analysis is of high interest. Generally speaking, social events, lifestyle and health are highly correlated, but there is a lack of tools to monitor and analyse them. We consider that egocentric vision provides a tool to obtain information and understand users social interactions. We propose a model that enables us to evaluate and visualize social traits obtained by analysing social interactions appearance within egocentric photostreams. Given sets of egocentric images, we detect the appearance of faces within the days of the camera wearer, and rely on clustering algorithms to group their feature descriptors in order to re-identify persons. Recurrence of detected faces within photostreams allows us to shape an idea of the social pattern of behaviour of the user. We validated our model over several weeks recorded by different camera wearers. Our findings indicate that social profiles are potentially useful for social behaviour interpretation. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MILAB; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ TCP2019 |
Serial |
3377 |
|
Permanent link to this record |
|
|
|
|
Author |
Alicia Fornes; Josep Llados; Joana Maria Pujadas-Mora |
|
|
Title |
Browsing of the Social Network of the Past: Information Extraction from Population Manuscript Images |
Type |
Book Chapter |
|
Year |
2020 |
Publication |
Handwritten Historical Document Analysis, Recognition, and Retrieval – State of the Art and Future Trends |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
World Scientific |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-981-120-323-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; 600.140; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ FLP2020 |
Serial |
3350 |
|
Permanent link to this record |
|
|
|
|
Author |
Antonio Lopez; David Vazquez; Gabriel Villalonga |
|
|
Title |
Data for Training Models, Domain Adaptation |
Type |
Book Chapter |
|
Year |
2018 |
Publication |
Intelligent Vehicles. Enabling Technologies and Future Developments |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
395–436 |
|
|
Keywords |
Driving simulator; hardware; software; interface; traffic simulation; macroscopic simulation; microscopic simulation; virtual data; training data |
|
|
Abstract |
Simulation can enable several developments in the field of intelligent vehicles. This chapter is divided into three main subsections. The first one deals with driving simulators. The continuous improvement of hardware performance is a well-known fact that is allowing the development of more complex driving simulators. The immersion in the simulation scene is increased by high fidelity feedback to the driver. In the second subsection, traffic simulation is explained as well as how it can be used for intelligent transport systems. Finally, it is rather clear that sensor-based perception and action must be based on data-driven algorithms. Simulation could provide data to train and test algorithms that are afterwards implemented in vehicles. These tools are explained in the third subsection. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 600.118 |
Approved |
no |
|
|
Call Number |
Admin @ si @ LVV2018 |
Serial |
3047 |
|
Permanent link to this record |
|
|
|
|
Author |
Jose M. Armingol; Jorge Alfonso; Nourdine Aliane; Miguel Clavijo; Sergio Campos-Cordobes; Arturo de la Escalera; Javier del Ser; Javier Fernandez; Fernando Garcia; Felipe Jimenez; Antonio Lopez; Mario Mata |
|
|
Title |
Environmental Perception for Intelligent Vehicles |
Type |
Book Chapter |
|
Year |
2018 |
Publication |
Intelligent Vehicles. Enabling Technologies and Future Developments |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
23–101 |
|
|
Keywords |
Computer vision; laser techniques; data fusion; advanced driver assistance systems; traffic monitoring systems; intelligent vehicles |
|
|
Abstract |
Environmental perception represents, because of its complexity, a challenge for Intelligent Transport Systems due to the great variety of situations and different elements that can happen in road environments and that must be faced by these systems. In connection with this, so far there are a variety of solutions as regards sensors and methods, so the results of precision, complexity, cost, or computational load obtained by these works are different. In this chapter some systems based on computer vision and laser techniques are presented. Fusion methods are also introduced in order to provide advanced and reliable perception systems. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 600.118 |
Approved |
no |
|
|
Call Number |
Admin @ si @AAA2018 |
Serial |
3046 |
|
Permanent link to this record |
|
|
|
|
Author |
Santiago Segui; Laura Igual; Fernando Vilariño; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria |
|
|
Title |
Diagnostic System for Intestinal Motility Disfunctions Using Video Capsule Endoscopy |
Type |
Book Chapter |
|
Year |
2008 |
Publication |
Computer Vision Systems. 6th International |
Abbreviated Journal |
|
|
|
Volume |
5008 |
Issue |
|
Pages |
251–260 |
|
|
Keywords |
|
|
|
Abstract |
Wireless Video Capsule Endoscopy is a clinical technique consisting of the analysis of images from the intestine which are pro- vided by an ingestible device with a camera attached to it. In this paper we propose an automatic system to diagnose severe intestinal motility disfunctions using the video endoscopy data. The system is based on the application of computer vision techniques within a machine learn- ing framework in order to obtain the characterization of diverse motil- ity events from video sequences. We present experimental results that demonstrate the effectiveness of the proposed system and compare them with the ground-truth provided by the gastroenterologists. |
|
|
Address |
Santorini (Greece) |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer-Verlag |
Place of Publication |
Berlin Heidelberg |
Editor |
A. Gasteratos, M. Vincze, and J.K. Tsotsos |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-540-79546-9 |
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
ICVS |
|
|
Notes |
OR; MV; MILAB; SIAI |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ SIV2008; IAM @ iam @ SIV2008 |
Serial |
962 |
|
Permanent link to this record |
|
|
|
|
Author |
German Ros; Laura Sellart; Gabriel Villalonga; Elias Maidanik; Francisco Molero; Marc Garcia; Adriana Cedeño; Francisco Perez; Didier Ramirez; Eduardo Escobar; Jose Luis Gomez; David Vazquez; Antonio Lopez |
|
|
Title |
Semantic Segmentation of Urban Scenes via Domain Adaptation of SYNTHIA |
Type |
Book Chapter |
|
Year |
2017 |
Publication |
Domain Adaptation in Computer Vision Applications |
Abbreviated Journal |
|
|
|
Volume |
12 |
Issue |
|
Pages |
227-241 |
|
|
Keywords |
SYNTHIA; Virtual worlds; Autonomous Driving |
|
|
Abstract |
Vision-based semantic segmentation in urban scenarios is a key functionality for autonomous driving. Recent revolutionary results of deep convolutional neural networks (DCNNs) foreshadow the advent of reliable classifiers to perform such visual tasks. However, DCNNs require learning of many parameters from raw images; thus, having a sufficient amount of diverse images with class annotations is needed. These annotations are obtained via cumbersome, human labour which is particularly challenging for semantic segmentation since pixel-level annotations are required. In this chapter, we propose to use a combination of a virtual world to automatically generate realistic synthetic images with pixel-level annotations, and domain adaptation to transfer the models learnt to correctly operate in real scenarios. We address the question of how useful synthetic data can be for semantic segmentation – in particular, when using a DCNN paradigm. In order to answer this question we have generated a synthetic collection of diverse urban images, named SYNTHIA, with automatically generated class annotations and object identifiers. We use SYNTHIA in combination with publicly available real-world urban images with manually provided annotations. Then, we conduct experiments with DCNNs that show that combining SYNTHIA with simple domain adaptation techniques in the training stage significantly improves performance on semantic segmentation. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer |
Place of Publication |
|
Editor |
Gabriela Csurka |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 600.085; 600.082; 600.076; 600.118 |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ RSV2017 |
Serial |
2882 |
|
Permanent link to this record |
|
|
|
|
Author |
Joana Maria Pujadas-Mora; Alicia Fornes; Josep Llados; Gabriel Brea-Martinez; Miquel Valls-Figols |
|
|
Title |
The Baix Llobregat (BALL) Demographic Database, between Historical Demography and Computer Vision (nineteenth–twentieth centuries |
Type |
Book Chapter |
|
Year |
2019 |
Publication |
Nominative Data in Demographic Research in the East and the West: monograph |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
29-61 |
|
|
Keywords |
|
|
|
Abstract |
The Baix Llobregat (BALL) Demographic Database is an ongoing database project containing individual census data from the Catalan region of Baix Llobregat (Spain) during the nineteenth and twentieth centuries. The BALL Database is built within the project ‘NETWORKS: Technology and citizen innovation for building historical social networks to understand the demographic past’ directed by Alícia Fornés from the Center for Computer Vision and Joana Maria Pujadas-Mora from the Center for Demographic Studies, both at the Universitat Autònoma de Barcelona, funded by the Recercaixa program (2017–2019).
Its webpage is http://dag.cvc.uab.es/xarxes/.The aim of the project is to develop technologies facilitating massive digitalization of demographic sources, and more specifically the padrones (local censuses), in order to reconstruct historical ‘social’ networks employing computer vision technology. Such virtual networks can be created thanks to the linkage of nominative records compiled in the local censuses across time and space. Thus, digitized versions of individual and family lifespans are established, and individuals and families can be located spatially. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-5-7996-2656-3 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ PFL2019 |
Serial |
3351 |
|
Permanent link to this record |
|
|
|
|
Author |
Antonio Lopez; W. Niessen; Joan Serrat; K. Nikolay; B. Ter Haar Romeny; Juan J. Villanueva; M. Viergerver |
|
|
Title |
New improvements in the multiscale analysis of trabecular bone patterns |
Type |
Book Chapter |
|
Year |
2000 |
Publication |
Pattern Recognition and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
251-260 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IOS Press |
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 |
ADAS |
Approved |
no |
|
|
Call Number |
Admin @ si @ |
Serial |
3418 |
|
Permanent link to this record |
|
|
|
|
Author |
Pedro Herruzo; Marc Bolaños; Petia Radeva |
|
|
Title |
Can a CNN Recognize Catalan Diet? |
Type |
Book Chapter |
|
Year |
2016 |
Publication |
AIP Conference Proceedings |
Abbreviated Journal |
|
|
|
Volume |
1773 |
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
CoRR abs/1607.08811
Nowadays, we can find several diseases related to the unhealthy diet habits of the population, such as diabetes, obesity, anemia, bulimia and anorexia. In many cases, these diseases are related to the food consumption of people. Mediterranean diet is scientifically known as a healthy diet that helps to prevent many metabolic diseases. In particular, our work focuses on the recognition of Mediterranean food and dishes. The development of this methodology would allow to analise the daily habits of users with wearable cameras, within the topic of lifelogging. By using automatic mechanisms we could build an objective tool for the analysis of the patient’s behavior, allowing specialists to discover unhealthy food patterns and understand the user’s lifestyle.
With the aim to automatically recognize a complete diet, we introduce a challenging multi-labeled dataset related to Mediter-ranean diet called FoodCAT. The first type of label provided consists of 115 food classes with an average of 400 images per dish, and the second one consists of 12 food categories with an average of 3800 pictures per class. This dataset will serve as a basis for the development of automatic diet recognition. In this context, deep learning and more specifically, Convolutional Neural Networks (CNNs), currently are state-of-the-art methods for automatic food recognition. In our work, we compare several architectures for image classification, with the purpose of diet recognition. Applying the best model for recognising food categories, we achieve a top-1 accuracy of 72.29%, and top-5 of 97.07%. In a complete diet recognition of dishes from Mediterranean diet, enlarged with the Food-101 dataset for international dishes recognition, we achieve a top-1 accuracy of 68.07%, and top-5 of 89.53%, for a total of 115+101 food classes. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ HBR2016 |
Serial |
2837 |
|
Permanent link to this record |
|
|
|
|
Author |
Agnes Borras; Josep Llados |
|
|
Title |
Object Image Retrieval by Shape Content in Complex Scenes Using Geometric Constraints |
Type |
Book Chapter |
|
Year |
2005 |
Publication |
Pattern Recognition And Image Analysis |
Abbreviated Journal |
LNCS |
|
|
Volume |
3522 |
Issue |
|
Pages |
325–332 |
|
|
Keywords |
|
|
|
Abstract |
This paper presents an image retrieval system based on 2D shape information. Query shape objects and database images are repre- sented by polygonal approximations of their contours. Afterwards they are encoded, using geometric features, in terms of predefined structures. Shapes are then located in database images by a voting procedure on the spatial domain. Then an alignment matching provides a probability value to rank de database image in the retrieval result. The method al- lows to detect a query object in database images even when they contain complex scenes. Also the shape matching tolerates partial occlusions and affine transformations as translation, rotation or scaling. |
|
|
Address |
Estoril (Portugal) |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Link |
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; |
Approved |
no |
|
|
Call Number |
DAG @ dag @ BoL2005; IAM @ iam @ BoL2005 |
Serial |
556 |
|
Permanent link to this record |
|
|
|
|
Author |
Anton Cervantes; Gemma Sanchez; Josep Llados; Agnes Borras; Ana Rodriguez |
|
|
Title |
Biometric Recognition Based on Line Shape Descriptors |
Type |
Book Chapter |
|
Year |
2006 |
Publication |
Lecture Notes in Computer Science |
Abbreviated Journal |
|
|
|
Volume |
3926 |
Issue |
|
Pages |
346–357, |
|
|
Keywords |
|
|
|
Abstract |
Abstract. In this paper we propose biometric descriptors inspired by shape signatures traditionally used in graphics recognition approaches. In particular several methods based on line shape descriptors used to iden- tify newborns from the biometric information of the ears are developed. The process steps are the following: image acquisition, ear segmentation, ear normalization, feature extraction and identification. Several shape signatures are defined from contour images. These are formulated in terms of zoning and contour crossings descriptors. Experimental results are presented to demonstrate the effectiveness of the used techniques. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Link |
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 |
Approved |
no |
|
|
Call Number |
DAG @ dag @ CSL2006 |
Serial |
685 |
|
Permanent link to this record |
|
|
|
|
Author |
Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Oscar Vilarroya; Petia Radeva |
|
|
Title |
A Supervised Graph-cut Deformable Model for Brain MRI Segmentation. Deformation models: tracking, animation and applications |
Type |
Book Chapter |
|
Year |
2012 |
Publication |
Computational Vision and Biomechanics |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Netherlands |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-94-007-5445-4 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MILAB;HuPBA |
Approved |
no |
|
|
Call Number |
Admin @ si @ ISH2012b |
Serial |
2066 |
|
Permanent link to this record |
|
|
|
|
Author |
Fernando Vilariño; Debora Gil; Petia Radeva |
|
|
Title |
A Novel FLDA Formulation for Numerical Stability Analysis |
Type |
Book Chapter |
|
Year |
2004 |
Publication |
Recent Advances in Artificial Intelligence Research and Development |
Abbreviated Journal |
|
|
|
Volume |
113 |
Issue |
|
Pages |
77-84 |
|
|
Keywords |
Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision |
|
|
Abstract |
Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IOS Press |
Place of Publication |
|
Editor |
J. Vitrià, P. Radeva and I. Aguiló |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-1-58603-466-5 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MV;IAM;MILAB;SIAI |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VGR2004 |
Serial |
1663 |
|
Permanent link to this record |