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Author Pau Rodriguez; Jordi Gonzalez; Josep M. Gonfaus; Xavier Roca edit   pdf
doi  openurl
  Title Integrating Vision and Language in Social Networks for Identifying Visual Patterns of Personality Traits Type Journal
  Year 2019 Publication International Journal of Social Science and Humanity Abbreviated Journal IJSSH  
  Volume (down) 9 Issue 1 Pages 6-12  
  Keywords  
  Abstract Social media, as a major platform for communication and information exchange, is a rich repository of the opinions and sentiments of 2.3 billion users about a vast spectrum of topics. In this sense, user text interactions are widely used to sense the whys of certain social user’s demands and cultural- driven interests. However, the knowledge embedded in the 1.8 billion pictures which are uploaded daily in public profiles has just started to be exploited. Following this trend on visual-based social analysis, we present a novel methodology based on neural networks to build a combined image-and-text based personality trait model, trained with images posted together with words found highly correlated to specific personality traits. So, the key contribution in this work is to explore whether OCEAN personality trait modeling can be addressed based on images, here called MindPics, appearing with certain tags with psychological insights. We found that there is a correlation between posted images and the personality estimated from their accompanying texts. Thus, the experimental results are consistent with previous cyber-psychology results based on texts, suggesting that images could also be used for personality estimation: classification results on some personality traits show that specific and characteristic visual patterns emerge, in essence representing abstract concepts. These results open new avenues of research for further refining the proposed personality model under the supervision of psychology experts, and to further substitute current textual personality questionnaires by image-based ones.  
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  Area Expedition Conference  
  Notes ISE; 600.119 Approved no  
  Call Number Admin @ si @ RGG2019 Serial 3414  
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Author Diego Velazquez; Josep M. Gonfaus; Pau Rodriguez; Xavier Roca; Seiichi Ozawa; Jordi Gonzalez edit  url
doi  openurl
  Title Logo Detection With No Priors Type Journal Article
  Year 2021 Publication IEEE Access Abbreviated Journal ACCESS  
  Volume (down) 9 Issue Pages 106998-107011  
  Keywords  
  Abstract In recent years, top referred methods on object detection like R-CNN have implemented this task as a combination of proposal region generation and supervised classification on the proposed bounding boxes. Although this pipeline has achieved state-of-the-art results in multiple datasets, it has inherent limitations that make object detection a very complex and inefficient task in computational terms. Instead of considering this standard strategy, in this paper we enhance Detection Transformers (DETR) which tackles object detection as a set-prediction problem directly in an end-to-end fully differentiable pipeline without requiring priors. In particular, we incorporate Feature Pyramids (FP) to the DETR architecture and demonstrate the effectiveness of the resulting DETR-FP approach on improving logo detection results thanks to the improved detection of small logos. So, without requiring any domain specific prior to be fed to the model, DETR-FP obtains competitive results on the OpenLogo and MS-COCO datasets offering a relative improvement of up to 30%, when compared to a Faster R-CNN baseline which strongly depends on hand-designed priors.  
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  Notes ISE Approved no  
  Call Number Admin @ si @ VGR2021 Serial 3664  
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Author Michael Holte; Bhaskar Chakraborty; Jordi Gonzalez; Thomas B. Moeslund edit   pdf
url  doi
openurl 
  Title A Local 3D Motion Descriptor for Multi-View Human Action Recognition from 4D Spatio-Temporal Interest Points Type Journal Article
  Year 2012 Publication IEEE Journal of Selected Topics in Signal Processing Abbreviated Journal J-STSP  
  Volume (down) 6 Issue 5 Pages 553-565  
  Keywords  
  Abstract In this paper, we address the problem of human action recognition in reconstructed 3-D data acquired by multi-camera systems. We contribute to this field by introducing a novel 3-D action recognition approach based on detection of 4-D (3-D space $+$ time) spatio-temporal interest points (STIPs) and local description of 3-D motion features. STIPs are detected in multi-view images and extended to 4-D using 3-D reconstructions of the actors and pixel-to-vertex correspondences of the multi-camera setup. Local 3-D motion descriptors, histogram of optical 3-D flow (HOF3D), are extracted from estimated 3-D optical flow in the neighborhood of each 4-D STIP and made view-invariant. The local HOF3D descriptors are divided using 3-D spatial pyramids to capture and improve the discrimination between arm- and leg-based actions. Based on these pyramids of HOF3D descriptors we build a bag-of-words (BoW) vocabulary of human actions, which is compressed and classified using agglomerative information bottleneck (AIB) and support vector machines (SVMs), respectively. Experiments on the publicly available i3DPost and IXMAS datasets show promising state-of-the-art results and validate the performance and view-invariance of the approach.  
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  Series Volume Series Issue Edition  
  ISSN 1932-4553 ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ HCG2012 Serial 1994  
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Author Hamdi Dibeklioglu; M.O. Hortas; I. Kosunen; P. Zuzánek; Albert Ali Salah; Theo Gevers edit  doi
openurl 
  Title Design and implementation of an affect-responsive interactive photo frame Type Journal
  Year 2011 Publication Journal on Multimodal User Interfaces Abbreviated Journal JMUI  
  Volume (down) 4 Issue 2 Pages 81-95  
  Keywords  
  Abstract This paper describes an affect-responsive interactive photo-frame application that offers its user a different experience with every use. It relies on visual analysis of activity levels and facial expressions of its users to select responses from a database of short video segments. This ever-growing database is automatically prepared by an offline analysis of user-uploaded videos. The resulting system matches its user’s affect along dimensions of valence and arousal, and gradually adapts its response to each specific user. In an extended mode, two such systems are coupled and feed each other with visual content. The strengths and weaknesses of the system are assessed through a usability study, where a Wizard-of-Oz response logic is contrasted with the fully automatic system that uses affective and activity-based features, either alone, or in tandem.  
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  Publisher Springer–Verlag Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1783-7677 ISBN Medium  
  Area Expedition Conference  
  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ DHK2011 Serial 1842  
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Author Albert Ali Salah; Theo Gevers; Nicu Sebe; Alessandro Vinciarelli edit  openurl
  Title Computer Vision for Ambient Intelligence Type Journal Article
  Year 2011 Publication Journal of Ambient Intelligence and Smart Environments Abbreviated Journal JAISE  
  Volume (down) 3 Issue 3 Pages 187-191  
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  Notes ISE Approved no  
  Call Number Admin @ si @ SGS2011a Serial 1725  
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