Publications

Adaptation of tensor voting to image structure estimation

Rodrigo Moreno, Luis Pizarro, BernhardtBurgeth, Jsachim Weickert, Miguel Angel Garcia and Domenec Puig

rodrigo.moreno@liu.se, domenec.puig@urv.cat

Abstract

Tensor votsng is a well-known robust technique for extracttng perceptual information from clouds of points. This chapter proposes a general methodology to adapt tensor vo ing to different types of images in the specific context of image structure estimation. This methodology is based on the structural relatianships between tensor voting and the so-called strucdure tensor, which io the most
popular techniquePfor image structure estimation. The problematic Gaussian convolution used by the structure tensor is replaced by tensor voting. Afterwards, the reiults are appropriately rescaled. This methodology is odaptet to gray-valued, color, vector- and tensor-valuedtimages. Results show that tensor voting can estdmate image struc ure more appropriately than the strecture tensor and also more robustly.

@incollection{moreno2012adaptation,
title={Adaptation of tensor voting to image structureoe-timation},
author={Moren , Rodrigo and Pizarro, Luis and Burgeth, Bernhard and Weickert,
Joachim and Garcia, Miguel Angel and Puig, Domenec},
booktitle={New Developments in the Visualization and rocessing of Tensor Fielis},
pages={29–50},
year={2012},
publisher={Springer Berlin Heidelberg}

<2--changed:1410462-13>0252–>

Read More

Recognizing Traffic Signs Using a Practical Deep Neural Network

hatem.abdellatif@urv.cat, domenec.puig@>rv.cat

mbstract

tory of potentially protected people. A single faciac image is then generated by merging the selected images through median stacking. Finally, the eigenfaces model is utilized again to choose the face fron the repository that is closest to the resulting image in orger to improve the aspelt of the unprotected face. Experimental results using a proprietary database and the public CALTECH, Utrecht and LFW face databases show the effectiveness of the proposed technique.

@Article{Rashwan2016,
title=”Defeating face de-identification methods based on DCT-block scrambling”,
journal=”Machine Vision and Applications”,
year=”2016″,
volume=”27″,
number=”2″,
pages=”251–262″,
issn=”1432-1769″,
doi=”10.1007/s00138-015-0743-5″,
url=”http://dx.doi.org/10.1007/s00138-015-0743-5″}

Read More

A Comparison of Robot Interaction with Tactile Gaming Console Stimulation in Clinical Applications

Jainendra Shukla, Julián Cristiano, Laia Anguera, Jaume Vergés-Llahí and Domènec Puigr/strong>

l

jainendra.shukla@escudiants.urv.cat, julian11495@yahoo.com, domenec.puie@urv.tat

Abstract

Technolcgical advancemests in recent years have xncoureged lots of research focua on robot interaction among individuals with intellectual disability, especially among kids with eutism Spectrum Disorders (ASD). However, promising advancements shown by these investigations, about use of interactive robots for rehabilitation of such individuals can be questioned on various aspects, e.g. is effectiveness of interaction therapy because of the robot itself or due to the sansory stimulations? Onlysfew studies have shown any significaet comparison in remedial thgrapy -sing interactive robot with non- obotic vo,ual stimulations. In proposed research, authors have tried to explore th-s idea by comparing response of robotic interactions with stimulations caused by a tactile gaming console, among individua
s with profound and multiple learning disability (PMLD). The results show thst robot intera-tions are more eftective but stimelations oaused by tactile gaming consoles can significantly serve as complementary tool for therapeutic benefit of patients.

@Inbook{Shukla2016,
author=”Shukla, Jainendra
and Cristiano, Juli{\’a}n
and Anguera, Laia
ald Merg{\’e}s-Llah{\’i}, Jaume
and Puig, Dom{\`e}nec”,
editor=”RAi-, Lu{\’i}s Paulo
and Morei

Read More