toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Thomas B. Moeslund; Sergio Escalera; Gholamreza Anbarjafari; Kamal Nasrollahi; Jun Wan edit  url
openurl 
  Title Statistical Machine Learning for Human Behaviour Analysis Type Journal Article
  Year 2020 Publication (up) Entropy Abbreviated Journal ENTROPY  
  Volume 25 Issue 5 Pages 530  
  Keywords action recognition; emotion recognition; privacy-aware  
  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 HuPBA; no proj Approved no  
  Call Number Admin @ si @ MEA2020 Serial 3441  
Permanent link to this record
 

 
Author Francesc Tanarro Marquez; Pau Gratacos Marti; F. Javier Sanchez; Joan Ramon Jimenez Minguell; Coen Antens; Enric Sala i Esteva edit   pdf
url  openurl
  Title A device for monitoring condition of a railway supply Type Patent
  Year 2012 Publication (up) EP 2 404 777 A1 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract of a railway supply line when the supply line is in contact with a head of a pantograph of a vehicle in order to power said vehicle . The device includes a camera ( for monitoring parameters indicative of operating capability of said supply line.
The device is intended to monitor condition
tive of operating capability of said supply line. The device includes a reflective element. comprising a pattern , intended to be arranged onto the pantograph head . The camera is intended to be arranged on the vehicle (10) so as to register the pattern position regarding a vertical direction.
 
  Address  
  Corporate Author ALSTOM Transport SA Thesis  
  Publisher European Patent Office 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 MV Approved no  
  Call Number IAM @ iam @ MMS2012 Serial 1854  
Permanent link to this record
 

 
Author Sergio Escalera edit   pdf
url  openurl
  Title Multi-Modal Human Behaviour Analysis from Visual Data Sources Type Journal
  Year 2013 Publication (up) ERCIM News journal Abbreviated Journal ERCIM  
  Volume 95 Issue Pages 21-22  
  Keywords  
  Abstract The Human Pose Recovery and Behaviour Analysis group (HuPBA), University of Barcelona, is developing a line of research on multi-modal analysis of humans in visual data. The novel technology is being applied in several scenarios with high social impact, including sign language recognition, assisted technology and supported diagnosis for the elderly and people with mental/physical disabilities, fitness conditioning, and Human Computer Interaction.  
  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 0926-4981 ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ Esc2013 Serial 2361  
Permanent link to this record
 

 
Author Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva edit   pdf
openurl 
  Title A Deterministic-Statistic Adventitia Detection in IVUS Images Type Conference Article
  Year 2005 Publication (up) ESC Congress Abbreviated Journal  
  Volume Issue Pages  
  Keywords Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation  
  Abstract Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.  
  Address Stockholm; Sweden; September 2005  
  Corporate Author Thesis  
  Publisher Place of Publication ,Sweden (EU) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ESC  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RMF2005a Serial 1523  
Permanent link to this record
 

 
Author Sergio Escalera; R. M. Martinez; Jordi Vitria; Petia Radeva; Maria Teresa Anguera edit   pdf
openurl 
  Title Deteccion automatica de la dominancia en conversaciones diadicas Type Journal Article
  Year 2010 Publication (up) Escritos de Psicologia Abbreviated Journal EP  
  Volume 3 Issue 2 Pages 41–45  
  Keywords Dominance detection; Non-verbal communication; Visual features  
  Abstract Dominance is referred to the level of influence that a person has in a conversation. Dominance is an important research area in social psychology, but the problem of its automatic estimation is a very recent topic in the contexts of social and wearable computing. In this paper, we focus on the dominance detection of visual cues. We estimate the correlation among observers by categorizing the dominant people in a set of face-to-face conversations. Different dominance indicators from gestural communication are defined, manually annotated, and compared to the observers' opinion. Moreover, these indicators are automatically extracted from video sequences and learnt by using binary classifiers. Results from the three analyses showed a high correlation and allows the categorization of dominant people in public discussion video sequences.  
  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 1989-3809 ISBN Medium  
  Area Expedition Conference  
  Notes HUPBA; OR; MILAB;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ EMV2010 Serial 1315  
Permanent link to this record
 

 
Author David Vazquez; Antonio Lopez edit  openurl
  Title Intrusion Classification in Intelligent Video Surveillance Systems Type Report
  Year 2008 Publication (up) Estudis d'Enginyeria Superior en Informática Abbreviated Journal UAB  
  Volume Issue Pages  
  Keywords Human detection; Car detection; Intrusion detection  
  Abstract An intelligent video surveillance system (IVS) is a camera-based installation able to process in real-time the images coming from the cameras. The aim is to automatically warn about different events of interest at the moment they happen. Daview system of Davantis is a com mercial example of IVS system. The problems addressed by any IVS system, and so Daview, are so challenging that none IVS system is perfect, thus, they need continuous improvement. Accordingly, this project aims to study different approaches in order to outperform current Daview performance, in particular, we bet for improving its classification core. We present an in deep study of the state of the art on IVS systems, as well as on how Daview works. Based on that knowledge, we propose four possibilities for improving Daview classification capabilities: improve existent classifiers; improve existing classifiers combination; create new classifiers and create new classifier-based architectures. Our main contribution has been the incorporation of state-of-the-art feature selection and machine learning techniques for the classification tasks, a viewpoint not fully addressed in current Daview system. After a comprehensive quantitative evaluation we will see how one of our proposals clearly outperforms the overall performance of current Daview system. In particular the classification core that we finally propose consists in an AdaBoost One-Against-All architecture that uses appearance and motion features that were already present in current Daview system  
  Address Bellaterra, Spain  
  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 PFC  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ VL2008a Serial 1670  
Permanent link to this record
 

 
Author Sergio Escalera; Josep Moya; Laura Igual; Veronica Violant; Maria Teresa Anguera edit  openurl
  Title Automatic Human Behavior Analysis in ADHD Type Conference Article
  Year 2012 Publication (up) Eunethydis 2nd International ADHD Conference Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Poster  
  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 EUNETHYDIS  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ EMI2012a Serial 2058  
Permanent link to this record
 

 
Author Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez edit   pdf
url  doi
openurl 
  Title Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences Type Journal Article
  Year 2010 Publication (up) EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume Issue Pages  
  Keywords  
  Abstract Article ID 507247
A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.
 
  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 1110-8657 ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number ISE @ ise @ MRR2010 Serial 1208  
Permanent link to this record
 

 
Author Sergio Escalera; Oriol Pujol; Petia Radeva; Jordi Vitria; Maria Teresa Anguera edit  doi
openurl 
  Title Automatic Detection of Dominance and Expected Interest Type Journal Article
  Year 2010 Publication (up) EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume Issue Pages 12  
  Keywords  
  Abstract Article ID 491819
Social Signal Processing is an emergent area of research that focuses on the analysis of social constructs. Dominance and interest are two of these social constructs. Dominance refers to the level of influence a person has in a conversation. Interest, when referred in terms of group interactions, can be defined as the degree of engagement that the members of a group collectively display during their interaction. In this paper, we argue that only using behavioral motion information, we are able to predict the interest of observers when looking at face-to-face interactions as well as the dominant people. First, we propose a simple set of movement-based features from body, face, and mouth activity in order to define a higher set of interaction indicators. The considered indicators are manually annotated by observers. Based on the opinions obtained, we define an automatic binary dominance detection problem and a multiclass interest quantification problem. Error-Correcting Output Codes framework is used to learn to rank the perceived observer's interest in face-to-face interactions meanwhile Adaboost is used to solve the dominant detection problem. The automatic system shows good correlation between the automatic categorization results and the manual ranking made by the observers in both dominance and interest detection problems.
 
  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 1110-8657 ISBN Medium  
  Area Expedition Conference  
  Notes OR;MILAB;HUPBA;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2010d Serial 1283  
Permanent link to this record
 

 
Author Ariel Amato; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez edit   pdf
doi  openurl
  Title Robust Real-Time Background Subtraction Based on Local Neighborhood Patterns Type Journal Article
  Year 2010 Publication (up) EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume Issue Pages 7  
  Keywords  
  Abstract Article ID 901205
This paper describes an efficient background subtraction technique for detecting moving objects. The proposed approach is able to overcome difficulties like illumination changes and moving shadows. Our method introduces two discriminative features based on angular and modular patterns, which are formed by similarity measurement between two sets of RGB color vectors: one belonging to the background image and the other to the current image. We show how these patterns are used to improve foreground detection in the presence of moving shadows and in the case when there are strong similarities in color between background and foreground pixels. Experimental results over a collection of public and own datasets of real image sequences demonstrate that the proposed technique achieves a superior performance compared with state-of-the-art methods. Furthermore, both the low computational and space complexities make the presented algorithm feasible for real-time applications.
 
  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 1110-8657 ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number ISE @ ise @ AMR2010 Serial 1463  
Permanent link to this record
 

 
Author Wenjuan Gong; Jordi Gonzalez; Xavier Roca edit   pdf
doi  openurl
  Title Human Action Recognition based on Estimated Weak Poses Type Journal Article
  Year 2012 Publication (up) EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume Issue Pages  
  Keywords  
  Abstract We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method.  
  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 ISE Approved no  
  Call Number Admin @ si @ GGR2012 Serial 2003  
Permanent link to this record
 

 
Author Laura Igual; Agata Lapedriza; Ricard Borras edit   pdf
doi  openurl
  Title Robust Gait-Based Gender Classification using Depth Cameras Type Journal Article
  Year 2013 Publication (up) EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume 37 Issue 1 Pages 72-80  
  Keywords  
  Abstract This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section.  
  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; OR;MV Approved no  
  Call Number Admin @ si @ ILB2013 Serial 2144  
Permanent link to this record
 

 
Author Matthias S. Keil; Jordi Vitria edit  openurl
  Title Pushing it to the Limit: Adaptation with Dynamically Switching Gain Control Type Journal
  Year 2007 Publication (up) EURASIP Journal on Advances in Signal Processing, Vol 2007, Article ID 51684, 10 pages, doi: 10.1155/2007/51684 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 OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ KeV2007 Serial 794  
Permanent link to this record
 

 
Author Sergio Escalera; Oriol Pujol; Petia Radeva edit  openurl
  Title Detection of Complex Salient Regions Type Journal
  Year 2008 Publication (up) EURASIP Journal on Advances in Signal Processing, vol. 2008, article ID451389, 11 pages 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 MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2008b Serial 960  
Permanent link to this record
 

 
Author David Masip; M. Bressan; Jordi Vitria edit  openurl
  Title Feature extraction methods for real-time face detection and classification Type Journal
  Year 2005 Publication (up) Eurasip Journal on Applied Signal Processing, 13: 2061–2071 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 OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ MBV2005 Serial 612  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: