@conference {cMoliner, title = {Weakly Supervised Semantic Segmentation for Remote Sensing Hyperspectral Imaging}, booktitle = {International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020)}, year = {2020}, month = {05/2020}, abstract = {

This paper studies the problem of training a semantic segmentation neural network with weak annotations, in order to be applied in aerial vegetation images from Teide National Park. It proposes a Deep Seeded Region Growing system which consists on training a semantic segmentation network from a set of seeds generated by a Support Vector Machine. A region growing algorithm module is applied to the seeds to progressively increase the pixel-level supervision. The proposed method performs better than an SVM, which is one of the most popular segmentation tools in remote sensing image applications.

}, author = {Eloi Moliner and Luis Salgueiro and Ver{\'o}nica Vilaplana} } @mastersthesis {xTubau, title = {Wav2Pix: Enhancement and Evaluation of a Speech-conditioned Image Generator}, year = {2019}, abstract = {

The interest for image synthesis has grown exponentially for the last years. Few years ago, it was invented a very powerful tool for this task: Generative Adversarial Networks (GANs). As its high performance in generating realistic images has been proved, nowadays many researchers are putting the focus on cross-modal learning.

Taking advantage of the huge amount of information we can extract from speech (such as identity, gender or emotional state), in this\  work\  we\  explore\  its\  potential\  to\  generate\  face\  images of a speaker by conditioning a GAN with his/her voice.\  We propose the enhancement and evaluation of a deep neural network that is trained from scratch in an end-to-end fashion, generating a face directly from the raw speech waveform without any additional identity information (e.g reference image or one-hot encoding).

This project focus on the enhancement of a previous model proposed by Francisco Roldan. As a result of a deep analysis on the former project strengths and weaknesses, we present a novel dataset collected for this work, with high-quality videos of ten youtubers with notable expressiveness in both the speech and visual signals. Besides, unlike in the preliminary project, four different techniques are proposed in order to assess the results.

}, author = {Tubau, Miquel}, editor = {Amanda Duarte and Xavier Gir{\'o}-i-Nieto} } @conference {cDuartea, title = {Wav2Pix: Speech-conditioned Face Generation using Generative Adversarial Networks}, booktitle = {ICASSP}, year = {2019}, month = {05/2019}, publisher = {IEEE}, organization = {IEEE}, address = {Brighton, UK}, abstract = {

Speech is a rich biometric signal that contains information\ about the identity, gender and emotional state of the speaker.\ In this work, we explore its potential to generate face images\ of a speaker by conditioning a Generative Adversarial\ Network (GAN) with raw speech input. We propose a deep\ neural network that is trained from scratch in an end-to-end\ fashion, generating a face directly from the raw speech waveform\ without any additional identity information (e.g reference\ image or one-hot encoding). Our model is trained in a\ self-supervised fashion by exploiting the audio and visual signals\ naturally aligned in videos. With the purpose of training\ from video data, we present a novel dataset collected for this\ work, with high-quality videos of ten youtubers with notable\ expressiveness in both the speech and visual signals.

}, doi = {10.1109/ICASSP.2019.8682970}, url = {http://hdl.handle.net/2117/167073}, author = {Amanda Duarte and Rold{\'a}n, Francisco and Tubau, Miquel and Escur, Janna and Pascual-deLaPuente, Santiago and Amaia Salvador and Mohedano, Eva and McGuinness, Kevin and Jordi Torres and Xavier Gir{\'o}-i-Nieto} } @conference {cFernandezb, title = {What is going on in the world? A display platform for media understanding}, booktitle = {IEEE Multimedia Information Processing and Retrieval (MIPR) Conference}, year = {2018}, month = {04/2018}, publisher = {IEEE}, organization = {IEEE}, address = {Miami, FL (USA)}, abstract = {

News broadcasters and on-line publishers daily generate a large amount of articles and videos describing events currently happening in the world. In this, work we present a system that automatically indexes videos from a library and links them to stories developing in the news. The user interface displays in an intuitive manner the links between\  videos and stories and allows navigation through related content by using associated tags. This interface is a powerful industrial tool for publishers to index, retrieve and visualize their video content. It helps them identify which topics require more attention or retrieve related content that{\textquoteright}s already been published about the stories.

}, doi = {https://doi.org/10.1109/MIPR.2018.00045}, url = {https://www.youtube.com/watch?v=eaXcB2X-5xY}, author = {Fern{\`a}ndez, D{\`e}lia and David Varas and Bou, Elisenda and Xavier Gir{\'o}-i-Nieto} } @conference {cLopez-Palmaa, title = {Who watches the watchers? Quality control of the human inspection in production lines using Visual Intensity of Attention}, booktitle = {SAAEI 2018}, year = {2018}, month = {07/2018}, address = {Barcelona}, abstract = {

On multiple occasions production lines require inspectors, human operators that visualize certain steps of the production and determine the quality of the resulting products. However, inspectors are subject to errors. We propose a method based on computer vision to decide if the inspector has used an adequate attention in the different points of inspection so that pieces that have not been verified can be marked for rejection or re-inspection. The method uses a top-view ceiling camera that computes the trajectories and areas of vision of the inspector, and determines which products have received the correct amount of attention. The resulting attention figure can be compared with the acceptance range in the inspection protocol to determine if the inspection is valid.

}, author = {Manuel L{\'o}pez-Palma and Morros, J.R. and Javier Gago and Montserrat Corbal{\'a}n} } @article {xReyes, title = {Where did I leave my phone ?}, year = {2016}, month = {06/2016}, institution = {4th Workshop on Egocentric (First-Person) Vision, CVPR 2016}, type = {Extended abstract}, address = {Las Vegas, NV, USA}, abstract = {

The interest of users in having their lives digitally recorded has grown in the last years thanks to the advances on wearable sensors.\ Wearable cameras are one of the most informative ones, but they generate large amounts of images that require automatic analysis to build useful applications upon them.\ In this work we explore the potential of these devices to find the last appearance of personal objects among the more than 2,000 images that are generated everyday.\ This application could help into developing personal assistants capable of helping users when they do not remember where they left their personal objects.\ We adapt a previous work on instance search to the specific domain of egocentric vision.

Extended abstract presented as poster in the 4th Workshop on Egocentric (First-Person) Vision,\ CVPR 2016.

}, author = {Reyes, Cristian and Mohedano, Eva and McGuinness, Kevin and O{\textquoteright}Connor, N. and Xavier Gir{\'o}-i-Nieto} } @conference {cReyes, title = {Where is my Phone? Personal Object Retrieval from Egocentric Images}, booktitle = {Lifelogging Tools and Applications Workshop in ACM Multimedia}, year = {2016}, month = {10/2016}, publisher = {ACM}, organization = {ACM}, address = {Amsterdam, The Netherlands}, abstract = {

This work presents a retrieval pipeline and evaluation scheme for the problem of finding the last appearance of personal objects in a large dataset of images captured from a wearable camera. Each personal object is modelled by a small set of images that define a query for a visual search engine.The retrieved results are reranked considering the temporal timestamps of the images to increase the relevance of the later detections. Finally, a temporal interleaving of the results is introduced for robustness against false detections. The Mean Reciprocal Rank is proposed as a metric to evaluate this problem. This application could help into developing personal assistants capable of helping users when they do not remember where they left their personal belongings.

}, doi = {http://dx.doi.org/10.1145/2983576.2983582}, url = {http://arxiv.org/abs/1608.08139}, author = {Reyes, Cristian and Mohedano, Eva and McGuinness, Kevin and Noel E. O{\textquoteright}Connor and Xavier Gir{\'o}-i-Nieto} } @conference {cPardas11, title = {Work in progress - Cooperative and competitive projects for engaging students in advanced ICT subjects}, booktitle = {41st Annual Frontiers in Education Conference}, year = {2011}, pages = {1{\textendash}3}, isbn = {3-540-76258-2}, doi = {10.1109/FIE.2011.6143032}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6143032\&tag=1}, author = {M. Pard{\`a}s and Bonafonte, A.} } @article {aSchelkens03, title = {Wavelet coding of volumetric medical datasets}, journal = {Medical Imaging, IEEE Transactions on}, volume = {22}, year = {2003}, month = {march}, pages = {441 -458}, abstract = {

Several techniques based on the three-dimensional (3-D) discrete cosine transform (DCT) have been proposed for volumetric data coding. These techniques fail to provide lossless coding coupled with quality and resolution scalability, which is a significant drawback for medical applications. This paper gives an overview of several state-of-the-art 3-D wavelet coders that do meet these requirements and proposes new compression methods exploiting the quadtree and block-based coding concepts, layered zero-coding principles, and context-based arithmetic coding. Additionally, a new 3-D DCT-based coding scheme is designed and used for benchmarking. The proposed wavelet-based coding algorithms produce embedded data streams that can be decoded up to the lossless level and support the desired set of functionality constraints. Moreover, objective and subjective quality evaluation on various medical volumetric datasets shows that the proposed algorithms provide competitive lossy and lossless compression results when compared with the state-of-the-art.

}, keywords = {Algorithms, Computer-Assisted, Data Compression, discrete cosine transforms, embedded coding, embedded data streams, functionality constraints, image coding, Image Enhancement, Image Interpretation, Imaging, JPEG2000, layered zero coding, lossless compression, medical diagnostic imaging, medical image compression, medical image processing, Numerical Analysis, objective quality evaluation, progressive image transmission, quadtree coding, reviews, Signal Processing, subjective quality evaluation, Three-Dimensional, volumetric coding, wavelet transforms}, issn = {0278-0062}, doi = {10.1109/TMI.2003.809582}, author = {Schelkens, P. and Munteanu, A. and Barbarien, J. and Galca, M. and Xavier Gir{\'o}-i-Nieto and Cornelis, J.} }