toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author (up) Victor Ponce; Sergio Escalera; Xavier Baro edit  doi
isbn  openurl
  Title Multi-modal Social Signal Analysis for Predicting Agreement in Conversation Settings Type Conference Article
  Year 2013 Publication 15th ACM International Conference on Multimodal Interaction Abbreviated Journal  
  Volume Issue Pages 495-502  
  Keywords  
  Abstract In this paper we present a non-invasive ambient intelligence framework for the analysis of non-verbal communication applied to conversational settings. In particular, we apply feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues coming from the fields of psychology and observational methodology. We test our methodology over data captured in victim-offender mediation scenarios. Using different state-of-the-art classification approaches, our system achieve upon 75% of recognition predicting agreement among the parts involved in the conversations, using as ground truth the experts opinions.  
  Address Sidney; Australia; December 2013  
  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 978-1-4503-2129-7 Medium  
  Area Expedition Conference ICMI  
  Notes HuPBA;MV Approved no  
  Call Number Admin @ si @ PEB2013 Serial 2488  
Permanent link to this record
 

 
Author (up) Vitaliy Konovalov; Albert Clapes; Sergio Escalera edit   pdf
openurl 
  Title Automatic Hand Detection in RGB-Depth Data Sequences Type Conference Article
  Year 2013 Publication 16th Catalan Conference on Artificial Intelligence Abbreviated Journal  
  Volume Issue Pages 91-100  
  Keywords  
  Abstract Detecting hands in multi-modal RGB-Depth visual data has become a challenging Computer Vision problem with several applications of interest. This task involves dealing with changes in illumination, viewpoint variations, the articulated nature of the human body, the high flexibility of the wrist articulation, and the deformability of the hand itself. In this work, we propose an accurate and efficient automatic hand detection scheme to be applied in Human-Computer Interaction (HCI) applications in which the user is seated at the desk and, thus, only the upper body is visible. Our main hypothesis is that hand landmarks remain at a nearly constant geodesic distance from an automatically located anatomical reference point.
In a given frame, the human body is segmented first in the depth image. Then, a
graph representation of the body is built in which the geodesic paths are computed from the reference point. The dense optical flow vectors on the corresponding RGB image are used to reduce ambiguities of the geodesic paths’ connectivity, allowing to eliminate false edges interconnecting different body parts. Finally, we are able to detect the position of both hands based on invariant geodesic distances and optical flow within the body region, without involving costly learning procedures.
 
  Address Vic; October 2013  
  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 CCIA  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ KCE2013 Serial 2323  
Permanent link to this record
 

 
Author (up) Volkmar Frinken; Andreas Fischer; Carlos David Martinez Hinarejos edit   pdf
doi  isbn
openurl 
  Title Handwriting Recognition in Historical Documents using Very Large Vocabularies Type Conference Article
  Year 2013 Publication 2nd International Workshop on Historical Document Imaging and Processing Abbreviated Journal  
  Volume Issue Pages 67-72  
  Keywords  
  Abstract Language models are used in automatic transcription system to resolve ambiguities. This is done by limiting the vocabulary of words that can be recognized as well as estimating the n-gram probability of the words in the given text. In the context of historical documents, a non-unified spelling and the limited amount of written text pose a substantial problem for the selection of the recognizable vocabulary as well as the computation of the word probabilities. In this paper we propose for the transcription of historical Spanish text to keep the corpus for the n-gram limited to a sample of the target text, but expand the vocabulary with words gathered from external resources. We analyze the performance of such a transcription system with different sizes of external vocabularies and demonstrate the applicability and the significant increase in recognition accuracy of using up to 300 thousand external words.  
  Address Washington; USA; August 2013  
  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 978-1-4503-2115-0 Medium  
  Area Expedition Conference HIP  
  Notes DAG; 600.056; 600.045; 600.061; 602.006; 602.101 Approved no  
  Call Number Admin @ si @ FFM2013 Serial 2296  
Permanent link to this record
 

 
Author (up) Wenjuan Gong edit  openurl
  Title 3D Motion Data aided Human Action Recognition and Pose Estimation Type Book Whole
  Year 2013 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract In this work, we explore human action recognition and pose estimation prob-
lems. Different from traditional works of learning from 2D images or video
sequences and their annotated output, we seek to solve the problems with ad-
ditional 3D motion capture information, which helps to fill the gap between 2D
image features and human interpretations.
We first compare two different schools of approaches commonly used for 3D
pose estimation from 2D pose configuration: modeling and learning methods.
By looking into experiments results and considering our problems, we fixed a
learning method as the following approaches to do pose estimation. We then
establish a framework by adding a module of detecting 2D pose configuration
from images with varied background, which widely extend the application of
the approach. We also seek to directly estimate 3D poses from image features,
instead of estimating 2D poses as a intermediate module. We explore a robust
input feature, which combined with the proposed distance measure, provides
a solution for noisy or corrupted inputs. We further utilize the above method
to estimate weak poses,which is a concise representation of the original poses
by using dimension deduction technologies, from image features. Weak pose
space is where we calculate vocabulary and label action types using a bog of
words pipeline. Temporal information of an action is taken into consideration by
considering several consecutive frames as a single unit for computing vocabulary
and histogram assignments.
 
  Address Barcelona  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Jordi Gonzalez;Xavier Roca  
  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 @ Gon2013 Serial 2279  
Permanent link to this record
 

 
Author (up) Xavier Baro; David Masip; Elena Planas; Julia Minguillon edit  openurl
  Title PeLP: Plataforma para el Aprendizaje de Lenguajes de Programación Type Miscellaneous
  Year 2013 Publication XV Jornadas de Enseñanza Universitaria de la Informatica 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 JENUI  
  Notes OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ BMP2013 Serial 2237  
Permanent link to this record
 

 
Author (up) Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers edit   pdf
openurl 
  Title Adapting Pedestrian Detection from Synthetic to Far Infrared Images Type Conference Article
  Year 2013 Publication ICCV Workshop on Visual Domain Adaptation and Dataset Bias Abbreviated Journal  
  Volume Issue Pages  
  Keywords Domain Adaptation; Far Infrared; Pedestrian Detection  
  Abstract We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes.  
  Address Sydney; Australia; December 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Sydney, Australy Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICCVW-VisDA  
  Notes ADAS; 600.054; 600.055; 600.057; 601.217;ISE Approved no  
  Call Number ADAS @ adas @ SRV2013 Serial 2334  
Permanent link to this record
 

 
Author (up) Zeynep Yucel; Albert Ali Salah; Çetin Meriçli; Tekin Meriçli; Roberto Valenti; Theo Gevers edit  doi
openurl 
  Title Joint Attention by Gaze Interpolation and Saliency Type Journal
  Year 2013 Publication IEEE Transactions on cybernetics Abbreviated Journal T-CIBER  
  Volume 43 Issue 3 Pages 829-842  
  Keywords  
  Abstract Joint attention, which is the ability of coordination of a common point of reference with the communicating party, emerges as a key factor in various interaction scenarios. This paper presents an image-based method for establishing joint attention between an experimenter and a robot. The precise analysis of the experimenter's eye region requires stability and high-resolution image acquisition, which is not always available. We investigate regression-based interpolation of the gaze direction from the head pose of the experimenter, which is easier to track. Gaussian process regression and neural networks are contrasted to interpolate the gaze direction. Then, we combine gaze interpolation with image-based saliency to improve the target point estimates and test three different saliency schemes. We demonstrate the proposed method on a human-robot interaction scenario. Cross-subject evaluations, as well as experiments under adverse conditions (such as dimmed or artificial illumination or motion blur), show that our method generalizes well and achieves rapid gaze estimation for establishing joint attention.  
  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 2168-2267 ISBN Medium  
  Area Expedition Conference  
  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ YSM2013 Serial 2363  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: