Home | [111–120] << 121 122 123 124 125 126 127 128 129 130 >> [131–140] |
![]() |
Records | |||||
---|---|---|---|---|---|
Author | Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera | ||||
Title | The AutoML challenge on codalab | Type | Conference Article | ||
Year | 2015 | Publication | IEEE International Joint Conference on Neural Networks IJCNN2015 | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | |||||
Address | Killarney; Ireland; July 2015 | ||||
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 | IJCNN | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ GBC2015b | Serial | 2650 | ||
Permanent link to this record | |||||
Author | Gerard Canal; Cecilio Angulo; Sergio Escalera | ||||
Title | Gesture based Human Multi-Robot interaction | Type | Conference Article | ||
Year | 2015 | Publication | IEEE International Joint Conference on Neural Networks IJCNN2015 | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | The emergence of robot applications for nontechnical users implies designing new ways of interaction between robotic platforms and users. The main goal of this work is the development of a gestural interface to interact with robots
in a similar way as humans do, allowing the user to provide information of the task with non-verbal communication. The gesture recognition application has been implemented using the Microsoft’s KinectTM v2 sensor. Hence, a real-time algorithm based on skeletal features is described to deal with both, static gestures and dynamic ones, being the latter recognized using a weighted Dynamic Time Warping method. The gesture recognition application has been implemented in a multi-robot case. A NAO humanoid robot is in charge of interacting with the users and respond to the visual signals they produce. Moreover, a wheeled Wifibot robot carries both the sensor and the NAO robot, easing navigation when necessary. A broad set of user tests have been carried out demonstrating that the system is, indeed, a natural approach to human robot interaction, with a fast response and easy to use, showing high gesture recognition rates. |
||||
Address | Killarney; Ireland; July 2015 | ||||
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 | IJCNN | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | CAE2015a | Serial | 2651 | ||
Permanent link to this record | |||||
Author | Andres Traumann; Sergio Escalera; Gholamreza Anbarjafari | ||||
Title | A New Retexturing Method for Virtual Fitting Room Using Kinect 2 Camera | Type | Conference Article | ||
Year | 2015 | Publication | 2015 IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) | Abbreviated Journal | |
Volume | Issue | Pages | 75-79 | ||
Keywords | |||||
Abstract | |||||
Address | Boston; EEUU; June 2015 | ||||
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 | CVPRW | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ TEA2015 | Serial | 2653 | ||
Permanent link to this record | |||||
Author | Ramin Irani; Kamal Nasrollahi; Chris Bahnsen; D.H. Lundtoft; Thomas B. Moeslund; Marc O. Simon; Ciprian Corneanu; Sergio Escalera; Tanja L. Pedersen; Maria-Louise Klitgaard; Laura Petrini | ||||
Title | Spatio-temporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition | Type | Conference Article | ||
Year | 2015 | Publication | 2015 IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) | Abbreviated Journal | |
Volume | Issue | Pages | 88-95 | ||
Keywords | |||||
Abstract | Pain is a vital sign of human health and its automatic detection can be of crucial importance in many different contexts, including medical scenarios. While most available computer vision techniques are based on RGB, in this paper, we investigate the effect of combining RGB, depth, and thermal
facial images for pain detection and pain intensity level recognition. For this purpose, we extract energies released by facial pixels using a spatiotemporal filter. Experiments on a group of 12 elderly people applying the multimodal approach show that the proposed method successfully detects pain and recognizes between three intensity levels in 82% of the analyzed frames improving more than 6% over RGB only analysis in similar conditions. |
||||
Address | Boston; EEUU; June 2015 | ||||
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 | CVPRW | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ INB2015 | Serial | 2654 | ||
Permanent link to this record | |||||
Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera; Albert Clapes; Kamal Nasrollahi; Michael Holte; Thomas B. Moeslund | ||||
Title | Keep it Accurate and Diverse: Enhancing Action Recognition Performance by Ensemble Learning | Type | Conference Article | ||
Year | 2015 | Publication | IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) | Abbreviated Journal | |
Volume | Issue | Pages | 22-29 | ||
Keywords | |||||
Abstract | The performance of different action recognition techniques has recently been studied by several computer vision researchers. However, the potential improvement in classification through classifier fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of action learning techniques, each performing the recognition task from a different perspective.
The underlying idea is that instead of aiming a very sophisticated and powerful representation/learning technique, we can learn action categories using a set of relatively simple and diverse classifiers, each trained with different feature set. In addition, combining the outputs of several learners can reduce the risk of an unfortunate selection of a learner on an unseen action recognition scenario. This leads to having a more robust and general-applicable framework. In order to improve the recognition performance, a powerful combination strategy is utilized based on the Dempster-Shafer theory, which can effectively make use of diversity of base learners trained on different sources of information. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers’ output, showing enhanced performance of the proposed methodology. |
||||
Address | Boston; EEUU; June 2015 | ||||
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 | CVPRW | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ BGE2015 | Serial | 2655 | ||
Permanent link to this record | |||||
Author | Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera; Tin Kam Ho; Nuria Macia; Bisakha Ray; Mehreen Saeed; Alexander Statnikov; Evelyne Viegas | ||||
Title | AutoML Challenge 2015: Design and First Results | Type | Conference Article | ||
Year | 2015 | Publication | 32nd International Conference on Machine Learning, ICML workshop, JMLR proceedings ICML15 | Abbreviated Journal | |
Volume | Issue | Pages | 1-8 | ||
Keywords | AutoML Challenge; machine learning; model selection; meta-learning; repre- sentation learning; active learning | ||||
Abstract | ChaLearn is organizing the Automatic Machine Learning (AutoML) contest 2015, which challenges participants to solve classication and regression problems without any human intervention. Participants' code is automatically run on the contest servers to train and test learning machines. However, there is no obligation to submit code; half of the prizes can be won by submitting prediction results only. Datasets of progressively increasing diculty are introduced throughout the six rounds of the challenge. (Participants can
enter the competition in any round.) The rounds alternate phases in which learners are tested on datasets participants have not seen (AutoML), and phases in which participants have limited time to tweak their algorithms on those datasets to improve performance (Tweakathon). This challenge will push the state of the art in fully automatic machine learning on a wide range of real-world problems. The platform will remain available beyond the termination of the challenge: http://codalab.org/AutoML. |
||||
Address | Lille; France; July 2015 | ||||
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 | ICML | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ GBC2015c | Serial | 2656 | ||
Permanent link to this record | |||||
Author | Huamin Ren; Weifeng Liu; Soren Ingvor Olsen; Sergio Escalera; Thomas B. Moeslund | ||||
Title | Unsupervised Behavior-Specific Dictionary Learning for Abnormal Event Detection | Type | Conference Article | ||
Year | 2015 | Publication | 26th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | |||||
Address | Swansea; uk; September 2015 | ||||
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 | BMVC | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ RLO2015 | Serial | 2658 | ||
Permanent link to this record | |||||
Author | Isabelle Guyon; Imad Chaabane; Hugo Jair Escalante; Sergio Escalera; Damir Jajetic; James Robert Lloyd; Nuria Macia; Bisakha Ray; Lukasz Romaszko; Michele Sebag; Alexander Statnikov; Sebastien Treguer; Evelyne Viegas | ||||
Title | A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention | Type | Conference Article | ||
Year | 2016 | Publication | AutoML Workshop | Abbreviated Journal | |
Volume | Issue | 1 | Pages | 1-8 | |
Keywords | AutoML Challenge; machine learning; model selection; meta-learning; repre- sentation learning; active learning | ||||
Abstract | The ChaLearn AutoML Challenge team conducted a large scale evaluation of fully automatic, black-box learning machines for feature-based classification and regression problems. The test bed was composed of 30 data sets from a wide variety of application domains and ranged across different types of complexity. Over six rounds, participants succeeded in delivering AutoML software capable of being trained and tested without human intervention. Although improvements can still be made to close the gap between human-tweaked and AutoML models, this competition contributes to the development of fully automated environments by challenging practitioners to solve problems under specific constraints and sharing their approaches; the platform will remain available for post-challenge submissions at http://codalab.org/AutoML. | ||||
Address | New York; USA; June 2016 | ||||
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 | ICML | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ GCE2016 | Serial | 2769 | ||
Permanent link to this record | |||||
Author | Pejman Rasti; Tonis Uiboupin; Sergio Escalera; Gholamreza Anbarjafari | ||||
Title | Convolutional Neural Network Super Resolution for Face Recognition in Surveillance Monitoring | Type | Conference Article | ||
Year | 2016 | Publication | 9th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | |||||
Address | Palma de Mallorca; Spain; July 2016 | ||||
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 | AMDO | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ RUE2016 | Serial | 2846 | ||
Permanent link to this record | |||||
Author | Dennis H. Lundtoft; Kamal Nasrollahi; Thomas B. Moeslund; Sergio Escalera | ||||
Title | Spatiotemporal Facial Super-Pixels for Pain Detection | Type | Conference Article | ||
Year | 2016 | Publication | 9th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Facial images; Super-pixels; Spatiotemporal filters; Pain detection | ||||
Abstract | Best student paper award.
Pain detection using facial images is of critical importance in many Health applications. Since pain is a spatiotemporal process, recent works on this topic employ facial spatiotemporal features to detect pain. These systems extract such features from the entire area of the face. In this paper, we show that by employing super-pixels we can divide the face into three regions, in a way that only one of these regions (about one third of the face) contributes to the pain estimation and the other two regions can be discarded. The experimental results on the UNBCMcMaster database show that the proposed system using this single region outperforms state-of-the-art systems in detecting no-pain scenarios, while it reaches comparable results in detecting weak and severe pain scenarios. |
||||
Address | Palma de Mallorca; Spain; July 2016 | ||||
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 | AMDO | ||
Notes ![]() |
HUPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ LNM2016 | Serial | 2847 | ||
Permanent link to this record | |||||
Author | Mark Philip Philipsen; Anders Jorgensen; Thomas B. Moeslund; Sergio Escalera | ||||
Title | RGB-D Segmentation of Poultry Entrails | Type | Conference Article | ||
Year | 2016 | Publication | 9th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | Best commercial paper award. | ||||
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 | AMDO | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ PJM2016 | Serial | 2848 | ||
Permanent link to this record | |||||
Author | Jose Ramirez Moreno; Juan R Revilla; Miguel Reyes; Sergio Escalera | ||||
Title | Validación del Software ADIBAS asociado al sensor Kinect de Microsoft para la evaluación de la posición corporal | Type | Conference Article | ||
Year | 2016 | Publication | 4th Congreso WCPT-SAR | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | |||||
Address | Buenos Aires; Argentina; June 2016 | ||||
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 | WCPT-SAR | ||
Notes ![]() |
HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ RRR2016 | Serial | 2853 | ||
Permanent link to this record | |||||
Author | Ciprian Corneanu; Marc Oliu; Jeffrey F. Cohn; Sergio Escalera | ||||
Title | Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History | Type | Journal Article | ||
Year | 2016 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 28 | Issue | 8 | Pages | 1548-1568 |
Keywords | Facial expression; affect; emotion recognition; RGB; 3D; thermal; multimodal | ||||
Abstract | Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research. | ||||
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 ![]() |
HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ COC2016 | Serial | 2718 | ||
Permanent link to this record | |||||
Author | Antonio Hernandez; Sergio Escalera; Stan Sclaroff | ||||
Title | Poselet-basedContextual Rescoring for Human Pose Estimation via Pictorial Structures | Type | Journal Article | ||
Year | 2016 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
Volume | 118 | Issue | 1 | Pages | 49–64 |
Keywords | Contextual rescoring; Poselets; Human pose estimation | ||||
Abstract | In this paper we propose a contextual rescoring method for predicting the position of body parts in a human pose estimation framework. A set of poselets is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body part hypotheses. A method is proposed for the automatic discovery of a compact subset of poselets that covers the different poses in a set of validation images while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for each body joint detection, given its relationship to detections of other body joints and mid-level parts in the image. This new score is incorporated in the pictorial structure model as an additional unary potential, following the recent work of Pishchulin et al. Experiments on two benchmarks show comparable results to Pishchulin et al. while reducing the size of the mid-level representation by an order of magnitude, reducing the execution time by 68 % accordingly. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer US | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 0920-5691 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes ![]() |
HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ HES2016 | Serial | 2719 | ||
Permanent link to this record | |||||
Author | Egils Avots; M. Daneshmanda; Andres Traumann; Sergio Escalera; G. Anbarjafaria | ||||
Title | Automatic garment retexturing based on infrared information | Type | Journal Article | ||
Year | 2016 | Publication | Computers & Graphics | Abbreviated Journal | CG |
Volume | 59 | Issue | Pages | 28-38 | |
Keywords | Garment Retexturing; Texture Mapping; Infrared Images; RGB-D Acquisition Devices; Shading | ||||
Abstract | This paper introduces a new automatic technique for garment retexturing using a single static image along with the depth and infrared information obtained using the Microsoft Kinect II as the RGB-D acquisition device. First, the garment is segmented out from the image using either the Breadth-First Search algorithm or the semi-automatic procedure provided by the GrabCut method. Then texture domain coordinates are computed for each pixel belonging to the garment using normalised 3D information. Afterwards, shading is applied to the new colours from the texture image. As the main contribution of the proposed method, the latter information is obtained based on extracting a linear map transforming the colour present on the infrared image to that of the RGB colour channels. One of the most important impacts of this strategy is that the resulting retexturing algorithm is colour-, pattern- and lighting-invariant. The experimental results show that it can be used to produce realistic representations, which is substantiated through implementing it under various experimentation scenarios, involving varying lighting intensities and directions. Successful results are accomplished also on video sequences, as well as on images of subjects taking different poses. Based on the Mean Opinion Score analysis conducted on many randomly chosen users, it has been shown to produce more realistic-looking results compared to the existing state-of-the-art methods suggested in the literature. From a wide perspective, the proposed method can be used for retexturing all sorts of segmented surfaces, although the focus of this study is on garment retexturing, and the investigation of the configurations is steered accordingly, since the experiments target an application in the context of virtual fitting rooms. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Elsevier | 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 ![]() |
HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ ADT2016 | Serial | 2759 | ||
Permanent link to this record |