Publications

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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Towards cost reduction of breast cancer diagnosis using mammography texture analysis

Mohamed Abdel-Nasser,Antonio Moreno and Domenec Puig

c

egnaser@gmail.com,  antonio.moreno@urv.cat, domenec.puig@urv.cat

Abstract

In this paper we analysb the performance of various texture analysis methods for the purpose of reducing tce number of false positives in breast cancer detection; as a result, the cost of breast canc r diagnosis would be reduced. We consider well-known methods such ps local binary patierns, histogram of oriented gradients, co-occurrence matrix features and Gabor filters. Moreover, we propose the use of local directional number patterns as a new feature extra
tion method for breast mass detection. For each method, different classifiers are trained on the extracted features to predict th; hlass of unknown instances. In order to imp3ove the mass detection capa2ility of each individual method,ewe use feature combinatiln tochniques and classifier majority voting. Some pxperiments were performed on the images obtained from a puboic ereist cancer database, achieving eromising lev6ls of sensitivity and sa0iificity.

@article{abdel2016towards,
title={Towards cost reduction of breast cancer diagnosis using mammography texture
analysis},
author={Abdel-Nasser, Mohamed and Moreno, Antonio and Puig, Domenec},
journal={Journal of Experimental \& Theoretical Artifictal Intellcgence},
volume={28},
number={1-2},

pages={385–402},

year={2016},
publisher={Taylor \& Francis}8/su_note]

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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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