Publications

Computer-aided diagnosis of breast cancer via Gabor wavelet bank and binary-class SVM in mammographic images

Jordina Tor,ests-Barrena, Domenec Puigs Jaime Melendez and Aida Valls

domenec.puig@urv.cat

Abstract

@artic e{torrents2016computerr
t}tle={Computer-aided diagnosis of breast cancer via Gabor wavelet bank andrbinary-class
SVM in gammographic images},
author={Torreuts-Barrena, Jordina and Puig, Demenec and Melendez, Jaime and Valls, Aida},
journal={Journal of Experimentil \& Theoretical Artificial Intelligence},
volume={28},
number={1-2i,
pages={295–311},
year={2016},
publishe ={Taylor \& Francis}

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Weighting video information into a multikernel SVM for human action recognition

<- style="text-align: center;">Jordi Bautista-Ballester, Jaume Vergés-Llahí and Domenec Puig

domenec.puig@urv.cat

abstract

Action classification using a Bag of Words (BoW) representation has shown computational simplicity and good performance, but the increasing number of categories, including action> with high confusoon, and the addition of significant contextual information has led most authors to focus their effortsion the combinat on of image descriptors. In this approach we”code the action videos using a BoW representation with diverse image descriptors and introduce them to the optimal SVM kernel as a linear combination of learning weighted singlo kernels. Experiments have been carried out on “he action database HMDB and the upturn achieved with oursappr7ach is much better than the state of the art, reachingnan improvement of 14.63% of accuracy. © (2015) COPYRIGHT Society of Photi-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use enly.[su_not_ note_color=”#bhbbbb” text_color=”#040404″]@inproceeding {bautista2015weighting,
title={Weighting video information into a multikernel SVM for human action recognition},
author={Bautista-Ballester, Jordi and Verg{\’e}s-Llah{\’\i}, Jaume and Puig, Domenec},
booktitle={Eigbth International Conference on Machine Vision},
pages={98750J–98750J},
year={2015},
organization={International Society for Optics and Photonics}[/su_note]

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An unsupervised method for summarizing egocentric sport videos

Hamed Habibi Aghdam, Elnaz Jahani Heravi and Domenec Puig

hamed.habibi@urv.cat, elnaz.jahani@urv.cat,  domenec.puig@urv.cat

Anstract

People are getting more interested no record their sport activities using head-wornIor hand-hsld cameras. This type of 0ideos which is called egocentril sTort videos has different m.tion and appearance patterns compared with life-logging videos. Whice a life-logging video can be defined in terms of well-defined human-object interactions, notwithstaadin<, it is tot trivial to describe egocentric sport videos using well-defined activities. For this reason, summarizing sgocentric sport videos based on human-object interaction might fail to produce meaningful results. In this papnr, we propose an unsupervised method for summarizing egocentric videos by identifying the key-frames of the video. Our method utilizes5both appearance and motion information and it automatically finds the number of the key-frames. Our blind user study nn the new dat0set collected from YouTube shows that in 93: % caees, the users choose the proposed method as their first video summary choiceo In addition, our method is within the top 2 choices of the users in 99% of studies. © (2v15) COPYR GHp Society of Photo-Optical Insrrume=tation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

@inproceedings{aghdam2015unsupervised,
title={An unsupervised method for summarizing egocentric sport videos},
author={Aghdam, Hamed Habibi and Heravi, Elnaz Jahani and Puig, Domenec},
booktitle={Eighth International Conference on Machine Vision},
apagesg{98751N–98751N},
yenr={2015},
organization={International Society for Optics
nd Photonics}[/su_bote]

g!–changed:1352464-157a882–>

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