@conference {cLinardos, title = {Temporal Saliency Adaptation in Egocentric Videos}, booktitle = {ECCV 2018 Workshop on Egocentric Perception, Interaction and Computing}, year = {2018}, month = {07/2018}, publisher = {Extended abstract}, organization = {Extended abstract}, address = {Munich, Germany}, abstract = {

}, author = {Linardos, Panagiotis and Mohedano, Eva and Chert{\'o}, M{\`o}nica and Gurrin, Cathal and Xavier Gir{\'o}-i-Nieto} } @mastersthesis {xReyesa, title = {Time-sensitive Egocentric Image Retrieval for Fidings Objects in Lifelogs}, year = {2016}, abstract = {

Advisors: Eva Mohedano (Insight DCU), Kevin McGuinness (Insight DCU) and\ Xavier Gir{\'o}-i-Nieto\ (UPC)

Studies: Bachelor degree in Science and Telecommunication Technologies Engineering at\ Telecom BCN-ETSETB\ from the Technical University of Catalonia (UPC)

Grade: A (9.4/10.0)

This work explores diverse practices for conducting an object search from large amounts of egocentric images taking into account their temporal information. The application of this technology is to identify where personal belongings were lost or forgotten. We develop a pipeline-structured system. Firstly, the images of the day being scanned are sorted based on their probability to depict the forgotten object. This stage is solved by applying an existing visual search engine based on deep learning features. Secondly, a learned threshold selects the top ranked images as candidates to contain the object. Finally the images are reranked based on temporal and diversity criteria. Furthermore, we build a validation environment for assessing the system{\textquoteright}s performance aiming to find the optimal configuration of its parameters. Due to the lack of related works to be compared with, this thesis proposes an novel evaluation framework and metric to assess the problem.

[Tfg cristian reyes] time sensitive egocentric image retrieval for finding objects in lifelogs from Xavier Giro
}, author = {Reyes, Cristian}, editor = {Mohedano, Eva and McGuinness, Kevin and Xavier Gir{\'o}-i-Nieto} } @conference {cMohedano12, title = {Teaching Students to Teach Computers}, booktitle = { International Congress on University Teaching and Innovation (CIDUI)}, year = {2012}, month = {07/2012}, abstract = {

This paper presents a Problem-Based Learning activity that introduce machine learning contents in a study plan that is based on electronics and signal processing subjects. The activity proposes students to follow the same evaluation protocols adopted in scientific challenges, where differents research groups test their own machine learning techniques on a common dataset and evaluation metrics. Teams of students adopt the role of a research group to develop their novel solution for classifying images depending on\ whether they represent a certain semantic concepts. Student must implement software solutions that are tested and presented in class to prove their performance and originalty. This paper includes a detailed evaluation of the workload and satisfaction activity, based on questionaries answered by the students.

}, keywords = {groups, machine learning, problem-based learning}, url = {http://hdl.handle.net/2117/16354}, author = {Mohedano, Eva and Xavier Gir{\'o}-i-Nieto} }