toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Hugo Jair Escalante; Sergio Escalera; Isabelle Guyon; Xavier Baro; Yagmur Gucluturk; Umut Guçlu; Marcel van Gerven edit  url
doi  openurl
  Title Explainable and Interpretable Models in Computer Vision and Machine Learning Type Book Whole
  Year 2018 Publication The Springer Series on Challenges in Machine Learning Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.
Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision.
This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following:

·Evaluation and Generalization in Interpretable Machine Learning
·Explanation Methods in Deep Learning
·Learning Functional Causal Models with Generative Neural Networks
·Learning Interpreatable Rules for Multi-Label Classification
·Structuring Neural Networks for More Explainable Predictions
·Generating Post Hoc Rationales of Deep Visual Classification Decisions
·Ensembling Visual Explanations
·Explainable Deep Driving by Visualizing Causal Attention
·Interdisciplinary Perspective on Algorithmic Job Candidate Search
·Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions
·Inherent Explainability Pattern Theory-based Video Event Interpretations
 
  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; no menciona Approved no  
  Call Number (down) Admin @ si @ EEG2018 Serial 3399  
Permanent link to this record
 

 
Author G.D. Evangelidis; Ferran Diego; Joan Serrat; Antonio Lopez edit   pdf
openurl 
  Title Slice Matching for Accurate Spatio-Temporal Alignment Type Conference Article
  Year 2011 Publication In ICCV Workshop on Visual Surveillance Abbreviated Journal  
  Volume Issue Pages  
  Keywords video alignment  
  Abstract Video synchronization and alignment is a rather recent topic in computer vision. It usually deals with the problem of aligning sequences recorded simultaneously by static, jointly- or independently-moving cameras. In this paper, we investigate the more difficult problem of matching videos captured at different times from independently-moving cameras, whose trajectories are approximately coincident or parallel. To this end, we propose a novel method that pixel-wise aligns videos and allows thus to automatically highlight their differences. This primarily aims at visual surveillance but the method can be adopted as is by other related video applications, like object transfer (augmented reality) or high dynamic range video. We build upon a slice matching scheme to first synchronize the sequences, while we develop a spatio-temporal alignment scheme to spatially register corresponding frames and refine the temporal mapping. We investigate the performance of the proposed method on videos recorded from vehicles driven along different types of roads and compare with related previous works.  
  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 VS  
  Notes ADAS Approved no  
  Call Number (down) Admin @ si @ EDS2011; ADAS @ adas @ eds2011a Serial 1861  
Permanent link to this record
 

 
Author Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva edit   pdf
openurl 
  Title All the people around me: face clustering in egocentric photo streams Type Conference Article
  Year 2017 Publication 24th International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages  
  Keywords face discovery; face clustering; deepmatching; bag-of-tracklets; egocentric photo-streams  
  Abstract arxiv1703.01790
Given an unconstrained stream of images captured by a wearable photo-camera (2fpm), we propose an unsupervised bottom-up approach for automatic clustering appearing faces into the individual identities present in these data. The problem is challenging since images are acquired under real world conditions; hence the visible appearance of the people in the images undergoes intensive variations. Our proposed pipeline consists of first arranging the photo-stream into events, later, localizing the appearance of multiple people in them, and
finally, grouping various appearances of the same person across different events. Experimental results performed on a dataset acquired by wearing a photo-camera during one month, demonstrate the effectiveness of the proposed approach for the considered purpose.
 
  Address Beijing; China; September 2017  
  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 ICIP  
  Notes MILAB; no menciona Approved no  
  Call Number (down) Admin @ si @ EDR2017 Serial 3025  
Permanent link to this record
 

 
Author J. Elder; Fadi Dornaika; Y. Hou; R. Goldstein edit  openurl
  Title Attentive wide-field sensing for visual telepresence and surveillance Type Book Chapter
  Year 2005 Publication L. Itti, G. Rees and J. Tsotsos (editors), Neurobiology of Attention, Academic Press / Elsevier Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  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 Approved no  
  Call Number (down) Admin @ si @ EDH2005 Serial 604  
Permanent link to this record
 

 
Author Anna Esposito; Italia Cirillo; Antonietta Esposito; Leopoldina Fortunati; Gian Luca Foresti; Sergio Escalera; Nikolaos Bourbakis edit  openurl
  Title Impairments in decoding facial and vocal emotional expressions in high functioning autistic adults and adolescents Type Conference Article
  Year 2020 Publication Faces and Gestures in E-health and welfare workshop Abbreviated Journal  
  Volume Issue Pages 667-674  
  Keywords  
  Abstract  
  Address Virtual; November 2020  
  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 FGW  
  Notes HUPBA Approved no  
  Call Number (down) Admin @ si @ ECE2020 Serial 3516  
Permanent link to this record
 

 
Author Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva; Bogdan Raducanu edit   pdf
doi  openurl
  Title Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction Type Journal Article
  Year 2012 Publication Sensors Abbreviated Journal SENS  
  Volume 12 Issue 2 Pages 1702-1719  
  Keywords  
  Abstract IF=1.77 (2010)
Social interactions are a very important component in peopleís lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Timesí Blogging Heads opinion blog.
The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The linksí weights are a measure of the ìinfluenceî a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.
 
  Address  
  Corporate Author Thesis  
  Publisher Molecular Diversity Preservation International 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; OR;HuPBA;MV Approved no  
  Call Number (down) Admin @ si @ EBV2012 Serial 1885  
Permanent link to this record
 

 
Author Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva edit  doi
isbn  openurl
  Title Traffic-Sign Recognition Systems Type Book Whole
  Year 2011 Publication SpringerBriefs in Computer Science Abbreviated Journal  
  Volume Issue Pages 5-13  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4471-2244-9 Medium  
  Area Expedition Conference  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number (down) Admin @ si @ EBP2011 Serial 1801  
Permanent link to this record
 

 
Author Sergio Escalera; Xavier Baro; Jordi Gonzalez; Miguel Angel Bautista; Meysam Madadi; Miguel Reyes; Victor Ponce; Hugo Jair Escalante; Jaime Shotton; Isabelle Guyon edit   pdf
doi  openurl
  Title ChaLearn Looking at People Challenge 2014: Dataset and Results Type Conference Article
  Year 2014 Publication ECCV Workshop on ChaLearn Looking at People Abbreviated Journal  
  Volume 8925 Issue Pages 459-473  
  Keywords Human Pose Recovery; Behavior Analysis; Action and in- teractions; Multi-modal gestures; recognition  
  Abstract This paper summarizes the ChaLearn Looking at People 2014 challenge data and the results obtained by the participants. The competition was split into three independent tracks: human pose recovery from RGB data, action and interaction recognition from RGB data sequences, and multi-modal gesture recognition from RGB-Depth sequences. For all the tracks, the goal was to perform user-independent recognition in sequences of continuous images using the overlapping Jaccard index as the evaluation measure. In this edition of the ChaLearn challenge, two large novel data sets were made publicly available and the Microsoft Codalab platform were used to manage the competition. Outstanding results were achieved in the three challenge tracks, with accuracy results of 0.20, 0.50, and 0.85 for pose recovery, action/interaction recognition, and multi-modal gesture recognition, respectively.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECCVW  
  Notes HuPBA; ISE; 600.063;MV Approved no  
  Call Number (down) Admin @ si @ EBG2014 Serial 2529  
Permanent link to this record
 

 
Author Sergio Escalera; Xavier Baro; Hugo Jair Escalante; Isabelle Guyon edit   pdf
openurl 
  Title ChaLearn Looking at People: A Review of Events and Resources Type Conference Article
  Year 2017 Publication 30th International Joint Conference on Neural Networks Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This paper reviews the historic of ChaLearn Looking at People (LAP) events. We started in 2011 (with the release of the first Kinect device) to run challenges related to human action/activity and gesture recognition. Since then we have regularly organized events in a series of competitions covering all aspects of visual analysis of humans. So far we have organized more than 10 international challenges and events in this field. This paper reviews associated events, and introduces the ChaLearn LAP platform where public resources (including code, data and preprints of papers) related to the organized events are available. We also provide a discussion on perspectives of ChaLearn LAP activities.  
  Address Anchorage; Alaska; USA; May 2017  
  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; 602.143 Approved no  
  Call Number (down) Admin @ si @ EBE2017 Serial 3012  
Permanent link to this record
 

 
Author Sergio Escalera; Stephane Ayache; Jun Wan; Meysam Madadi; Umut Guçlu; Xavier Baro edit  url
doi  openurl
  Title Inpainting and Denoising Challenges Type Book Whole
  Year 2019 Publication The Springer Series on Challenges in Machine Learning Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract The problem of dealing with missing or incomplete data in machine learning and computer vision arises in many applications. Recent strategies make use of generative models to impute missing or corrupted data. Advances in computer vision using deep generative models have found applications in image/video processing, such as denoising, restoration, super-resolution, or inpainting.
Inpainting and Denoising Challenges comprises recent efforts dealing with image and video inpainting tasks. This includes winning solutions to the ChaLearn Looking at People inpainting and denoising challenges: human pose recovery, video de-captioning and fingerprint restoration.
This volume starts with a wide review on image denoising, retracing and comparing various methods from the pioneer signal processing methods, to machine learning approaches with sparse and low-rank models, and recent deep learning architectures with autoencoders and variants. The following chapters present results from the Challenge, including three competition tasks at WCCI and ECML 2018. The top best approaches submitted by participants are described, showing interesting contributions and innovating methods. The last two chapters propose novel contributions and highlight new applications that benefit from image/video inpainting.
 
  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; no menciona Approved no  
  Call Number (down) Admin @ si @ EAW2019 Serial 3398  
Permanent link to this record
 

 
Author Anna Esposito; Terry Amorese; Nelson Maldonato; Alessandro Vinciarelli; Maria Ines Torres; Sergio Escalera; Gennaro Cordasco edit  openurl
  Title Seniors’ ability to decode differently aged facial emotional expressions Type Conference Article
  Year 2020 Publication Faces and Gestures in E-health and welfare workshop Abbreviated Journal  
  Volume Issue Pages 716-722  
  Keywords  
  Abstract  
  Address Virtual; November 2020  
  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 FGW  
  Notes HUPBA Approved no  
  Call Number (down) Admin @ si @ EAM2020 Serial 3515  
Permanent link to this record
 

 
Author Sergio Escalera; Vassilis Athitsos; Isabelle Guyon edit  openurl
  Title Challenges in Multi-modal Gesture Recognition Type Book Chapter
  Year 2017 Publication Abbreviated Journal  
  Volume Issue Pages 1-60  
  Keywords Gesture recognition; Time series analysis; Multimodal data analysis; Computer vision; Pattern recognition; Wearable sensors; Infrared cameras; Kinect TMTM  
  Abstract This paper surveys the state of the art on multimodal gesture recognition and introduces the JMLR special topic on gesture recognition 2011–2015. We began right at the start of the Kinect TMTM revolution when inexpensive infrared cameras providing image depth recordings became available. We published papers using this technology and other more conventional methods, including regular video cameras, to record data, thus providing a good overview of uses of machine learning and computer vision using multimodal data in this area of application. Notably, we organized a series of challenges and made available several datasets we recorded for that purpose, including tens of thousands of videos, which are available to conduct further research. We also overview recent state of the art works on gesture recognition based on a proposed taxonomy for gesture recognition, discussing challenges 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; no proj Approved no  
  Call Number (down) Admin @ si @ EAG2017 Serial 3008  
Permanent link to this record
 

 
Author Sergio Escalera; Vassilis Athitsos; Isabelle Guyon edit  url
openurl 
  Title Challenges in multimodal gesture recognition Type Journal Article
  Year 2016 Publication Journal of Machine Learning Research Abbreviated Journal JMLR  
  Volume 17 Issue Pages 1-54  
  Keywords Gesture Recognition; Time Series Analysis; Multimodal Data Analysis; Computer Vision; Pattern Recognition; Wearable sensors; Infrared Cameras; KinectTM  
  Abstract This paper surveys the state of the art on multimodal gesture recognition and introduces the JMLR special topic on gesture recognition 2011-2015. We began right at the start of the KinectTMrevolution when inexpensive infrared cameras providing image depth recordings became available. We published papers using this technology and other more conventional methods, including regular video cameras, to record data, thus providing a good overview of uses of machine learning and computer vision using multimodal data in this area of application. Notably, we organized a series of challenges and made available several datasets we recorded for that purpose, including tens of thousands
of videos, which are available to conduct further research. We also overview recent state of the art works on gesture recognition based on a proposed taxonomy for gesture recognition, discussing challenges and future lines of research.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Zhuowen Tu  
  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 (down) Admin @ si @ EAG2016 Serial 2764  
Permanent link to this record
 

 
Author Rada Deeb; Joost Van de Weijer; Damien Muselet; Mathieu Hebert; Alain Tremeau edit   pdf
url  openurl
  Title Deep spectral reflectance and illuminant estimation from self-interreflections Type Journal Article
  Year 2019 Publication Journal of the Optical Society of America A Abbreviated Journal JOSA A  
  Volume 31 Issue 1 Pages 105-114  
  Keywords  
  Abstract In this work, we propose a convolutional neural network based approach to estimate the spectral reflectance of a surface and spectral power distribution of light from a single RGB image of a V-shaped surface. Interreflections happening in a concave surface lead to gradients of RGB values over its area. These gradients carry a lot of information concerning the physical properties of the surface and the illuminant. Our network is trained with only simulated data constructed using a physics-based interreflection model. Coupling interreflection effects with deep learning helps to retrieve the spectral reflectance under an unknown light and to estimate spectral power distribution of this light as well. In addition, it is more robust to the presence of image noise than classical approaches. Our results show that the proposed approach outperforms state-of-the-art learning-based approaches on simulated data. In addition, it gives better results on real data compared to other interreflection-based approaches.  
  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 LAMP; 600.120 Approved no  
  Call Number (down) Admin @ si @ DWM2019 Serial 3362  
Permanent link to this record
 

 
Author Michal Drozdzal; Jordi Vitria; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva edit  doi
openurl 
  Title Intestinal event segmentation for endoluminal video analysis Type Conference Article
  Year 2014 Publication 21st IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages 3592 - 3596  
  Keywords  
  Abstract  
  Address Paris; Francia; October 2014  
  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 ICIP  
  Notes MILAB; OR;MV Approved no  
  Call Number (down) Admin @ si @ DVS2014 Serial 2565  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: