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

Recent Submissions

  • Temporally coherent 3D point cloud video segmentation in generic scenes 

    Lin, Xiao; Casas Pla, Josep Ramon; Pardàs Feliu, Montse (2018-03-02)
    Article
    Open Access
    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)
    Conference lecture
    Restricted access - publisher's policy
    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
    Restricted access - publisher's policy
    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)
    Conference lecture
    Open Access
    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
    Restricted access - publisher's policy
  • Masked V-Net: an approach to brain tumor segmentation 

    Catà, Marcel; Casamitjana Díaz, Adrià; Sanchez Muriana, Irina; Combalia, Marc; Vilaplana Besler, Verónica (2017)
    Conference lecture
    Restricted access - publisher's policy
    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)
    Conference report
    Open Access
    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, ...
  • Skip RNN: learning to skip state updates in recurrent neural networks 

    Campos Camunez, Victor; Jou, Brendan; Giró Nieto, Xavier; Torres Viñals, Jordi; Chang, Shih-Fu (2018)
    Conference lecture
    Open Access
    Recurrent Neural Networks (RNNs) continue to show outstanding performance in sequence modeling tasks. However, training RNNs on long sequences often face challenges like slow inference, vanishing gradients and difficulty ...
  • Foreground objects segmentation for moving camera scenarios based on SCGMM 

    Gallego Vila, Jaime; Pardàs Feliu, Montse; Solano, Montse (2011)
    Conference report
    Restricted access - publisher's policy
    In this paper we present a new system for segmenting non-rigid objects in moving camera sequences for indoor and outdoor scenarios that achieves a correct object segmentation via global MAP-MRF framework formulation for ...
  • Motion analysis of image sequences using connected operators 

    Garrido Ostermann, Luis; Oliveras Vergés, Albert; Salembier Clairon, Philippe Jean (International Society for Photo-Optical Instrumentation Engineers (SPIE), 1997)
    Conference report
    Restricted access - publisher's policy
    This paper deals with a class of morphological operators called connected operators. These operators interact with the signal by merging flat zones. As a results, they do not create any new contours and are very attractive ...
  • Active mesh coding and rate-distortion theory 

    Salembier Clairon, Philippe Jean; Martí Navarro, Eva; Pardàs Feliu, Montse (Institute of Electrical and Electronics Engineers (IEEE), 1996)
    Conference lecture
    Open Access
    This paper presents a video coding scheme for very low bit rate applications. The coding approach relies on active meshes and can be viewed as a particular case of region-based coding. The active mesh is used to efficiently ...
  • Report on interim demonstration. FascinatE deliverable D6.2.1 

    Schreer, Oliver; Thomas, Graham; Thallinger, Georg; Kienast, Gert; Oldfield, Rob; Ruiz Hidalgo, Javier; Macq, Jean François (2012-07-25)
    External research report
    Open Access

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