El GPI fa recerca en Processament d'Imatge i Vídeo per representació, codificació, indexació i anàlisi del contingut visual. L'expertesa del grup en Morfologia i segmentació ha estat la base de contribucions als estàndards ISO MPEG-4 i MPEG-7. La recerca en anàlisi d’imatge l'ha permès participar en projectes europeus des de 1992 als programes RACE (Morpheco, coord.), ACTS (MAVT, MoMuSys, Vidas), IST (Diceman, Hypermedia, INTERFACE, ADViSOR, MASCOT, FAETHON), xarxes d'excel•lència (SCHEMA, SIMILAR, MUSCLE), i projectes integrats FP6 (CHIL) i FP7 (FASCINATE). El grup ha construit dues smart rooms al Campus Nord de la UPC, i ha fet contribucions en anàlisi visual per interacció, així com en aplicacions d’imatge biomèdica i teledetecció. Ha signat convenis de recerca amb empreses com Philips (París), France Telecom (Rennes), NXP (Holanda), Thomson (Princeton, USA), Alterface (Bèlgica) i nacionals com Telefònica, CCRTV, MediaPro, Fundació CELLEX, Hospital Clínic, AD Telecom o Abertis.

http://futur.upc.edu/GPI

Enviaments recents

  • Oriented trajectories as a method for audience measurement 

    López Palma, Manuel; Morros Rubió, Josep Ramon; Gago Barrio, Javier; Corbalán Fuertes, Montserrat (2018)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    The quantification of the attention received by advertisements is of paramount importance to determine its effectiveness. In this work, a simple and effective objective method for the assessment of the attention given to ...
  • Seabed mapping in coastal shallow waters using high resolution multispectral and hyperspectral imagery 

    Marcello, Javier; Eugenio, Francisco; Martín Abasolo, Javier; Marqués Acosta, Fernando (Multidisciplinary Digital Publishing Institute (MDPI), 2018-08-01)
    Article
    Accés obert
    Coastal ecosystems experience multiple anthropogenic and climate change pressures. To monitor the variability of the benthic habitats in shallow waters, the implementation of effective strategies is required to support ...
  • Detection-aided liver lesion segmentation using deep learning 

    Bellver, Míriam; Maninis, Kevis-Kokitsi; Pont Tuset, Jordi; Giró Nieto, Xavier; Torres Viñals, Jordi; Van Gool, Luc (2017)
    Comunicació de congrés
    Accés obert
    A fully automatic technique for segmenting the liver and localizing its unhealthy tissues is a convenient tool in order to diagnose hepatic diseases and assess the response to the according treatments. In this work we ...
  • What is going on in the world? A display platform for media understanding 

    Fernàndez, Dèlia; Varas, David; Espadaler, Joan; Masuda, Issey; Giró Nieto, Xavier; Riveiro, Juan Carlos; Bou Balust, Elisenda (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    Text en actes de congrés
    Accés restringit per política de l'editorial
    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 ...
  • Cascaded V-Net using ROI masks for brain tumor segmentation 

    Casamitjana Díaz, Adrià; Catà, Marcel; Sanchez Muriana, Irina; Combalia, Marc; Vilaplana Besler, Verónica (Springer, 2018)
    Capítol de llibre
    Accés restringit per política de l'editorial
    This book constitutes revised selected papers from the Third International MICCAI Brainlesion Workshop, BrainLes 2017, as well as the International Multimodal Brain Tumor Segmentation, BraTS, and White Matter Hyperintensities, ...
  • Temporally coherent 3D point cloud video segmentation in generic scenes 

    Lin, Xiao; Casas Pla, Josep Ramon; Pardàs Feliu, Montse (2018-03-02)
    Article
    Accés obert
    Video segmentation is an important building block for high level applications, such as scene understanding and interaction analysis. While outstanding results are achieved in this field by the state-of-the-art learning and ...
  • 3D point cloud segmentation using a fully connected conditional random field 

    Lin, Xiao; Casas Pla, Josep Ramon; Pardàs Feliu, Montse (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Comunicació de congrés
    Accés restringit per política de l'editorial
    Traditional image segmentation methods working with low level image features are usually difficult to adapt to higher level tasks, such as object recognition and scene understanding. Object segmentation emerges as a new ...
  • Scanpath and saliency prediction on 360 degree images 

    Assens Reina, Marc; Giró Nieto, Xavier; McGuinness, Kevin; O'Connor, Noel (2018-06-23)
    Article
    Accés restringit per política de l'editorial
    We introduce deep neural networks for scanpath and saliency prediction trained on 360-degree images. The scanpath prediction model called SaltiNet is based on a temporal-aware novel representation of saliency information ...
  • An interactive lifelog search engine for LSC2018 

    Alsina, Adrià; Giró Nieto, Xavier; Gurrin, Cathal (Association for Computing Machinery (ACM), 2018)
    Comunicació de congrés
    Accés obert
    In this work, we describe an interactive lifelog search engine developed for the LSC 2018 search challenge at ACM ICMR 2018. The paper introduces the four-step process required to support lifelog search engines and describes ...
  • Introduction to the special issue: egocentric vision and lifelogging 

    Dimiccoli, Mariella; Gurrin, Cathal; Crandall, David; Giró Nieto, Xavier; Radeva, Petia (2018-06-15)
    Article
    Accés restringit per política de l'editorial
  • Masked V-Net: an approach to brain tumor segmentation 

    Catà, Marcel; Casamitjana Díaz, Adrià; Sanchez Muriana, Irina; Combalia, Marc; Vilaplana Besler, Verónica (2017)
    Comunicació de congrés
    Accés restringit per política de l'editorial
    This paper introduces Masked V-Net architecture, a variant of the recently introduced V-Net[13] that reformulates the residual connections and uses a ROI mask to constrain the network to train only on relevant voxels. ...
  • Comparing fixed and adaptive computation time for recurrent neural networks 

    Fojo, Daniel; Campos Camunez, Victor; Giró Nieto, Xavier (2018)
    Text en actes de congrés
    Accés obert
    Deep networks commonly perform better than shallow ones, but allocating the proper amount of computation for each particular input sample remains an open problem. This issue is particularly challenging in sequential tasks, ...

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