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Author Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu edit   pdf
url  doi
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  Title New Opportunities for Computer Vision-Based Assistive Technology Systems for the Visually Impaired Type Journal Article
  Year 2014 Publication Computer Abbreviated Journal COMP  
  Volume (up) 47 Issue 4 Pages 52-58  
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  Abstract Computing advances and increased smartphone use gives technology system designers greater flexibility in exploiting computer vision to support visually impaired users. Understanding these users' needs will certainly provide insight for the development of improved usability of computing devices.  
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  ISSN 0018-9162 ISBN Medium  
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  Notes OR;MV Approved no  
  Call Number Admin @ si @ TSR2014a Serial 2317  
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Author Bogdan Raducanu; Fadi Dornaika edit   pdf
doi  openurl
  Title Embedding new observations via sparse-coding for non-linear manifold learning Type Journal Article
  Year 2014 Publication Pattern Recognition Abbreviated Journal PR  
  Volume (up) 47 Issue 1 Pages 480-492  
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  Abstract Non-linear dimensionality reduction techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data-the out-of-sample problem. For the first aspect, the proposed solutions, in general, were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only achieved for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that the sparse representation theory not only serves for automatic graph construction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the K-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on six public face datasets. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes.  
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  Notes OR;MV Approved no  
  Call Number Admin @ si @ RaD2013b Serial 2316  
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Author Gloria Fernandez Esparrach; Jorge Bernal; Maria Lopez Ceron; Henry Cordova; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; F. Javier Sanchez edit   pdf
doi  openurl
  Title Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps Type Journal Article
  Year 2016 Publication Endoscopy Abbreviated Journal END  
  Volume (up) 48 Issue 9 Pages 837-842  
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  Abstract Background and aims: Polyp miss-rate is a drawback of colonoscopy that increases significantly in small polyps. We explored the efficacy of an automatic computer vision method for polyp detection.
Methods: Our method relies on a model that defines polyp boundaries as valleys of image intensity. Valley information is integrated into energy maps which represent the likelihood of polyp presence.
Results: In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. Mean values of the maximum of energy map were higher in frames with polyps than without (p<0.001). Performance improved in high quality frames (AUC= 0.79, 95%CI: 0.70-0.87 vs 0.75, 95%CI: 0.66-0.83). Using 3.75 as maximum threshold value, sensitivity and specificity for detection of polyps were 70.4% (95%CI: 60.3-80.8) and 72.4% (95%CI: 61.6-84.6), respectively.
Conclusion: Energy maps showed a good performance for colonic polyp detection. This indicates a potential applicability in clinical practice.
 
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  Notes MV; Approved no  
  Call Number Admin @ si @FBL2016 Serial 2778  
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Author Antonio Hernandez; Miguel Angel Bautista; Xavier Perez Sala; Victor Ponce; Sergio Escalera; Xavier Baro; Oriol Pujol; Cecilio Angulo edit   pdf
doi  openurl
  Title Probability-based Dynamic Time Warping and Bag-of-Visual-and-Depth-Words for Human Gesture Recognition in RGB-D Type Journal Article
  Year 2014 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume (up) 50 Issue 1 Pages 112-121  
  Keywords RGB-D; Bag-of-Words; Dynamic Time Warping; Human Gesture Recognition  
  Abstract PATREC5825
We present a methodology to address the problem of human gesture segmentation and recognition in video and depth image sequences. A Bag-of-Visual-and-Depth-Words (BoVDW) model is introduced as an extension of the Bag-of-Visual-Words (BoVW) model. State-of-the-art RGB and depth features, including a newly proposed depth descriptor, are analysed and combined in a late fusion form. The method is integrated in a Human Gesture Recognition pipeline, together with a novel probability-based Dynamic Time Warping (PDTW) algorithm which is used to perform prior segmentation of idle gestures. The proposed DTW variant uses samples of the same gesture category to build a Gaussian Mixture Model driven probabilistic model of that gesture class. Results of the whole Human Gesture Recognition pipeline in a public data set show better performance in comparison to both standard BoVW model and DTW approach.
 
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  Notes HuPBA;MV; 605.203 Approved no  
  Call Number Admin @ si @ HBP2014 Serial 2353  
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Author Cristina Sanchez Montes; F. Javier Sanchez; Jorge Bernal; Henry Cordova; Maria Lopez Ceron; Miriam Cuatrecasas; Cristina Rodriguez de Miguel; Ana Garcia Rodriguez; Rodrigo Garces Duran; Maria Pellise; Josep Llach; Gloria Fernandez Esparrach edit   pdf
doi  openurl
  Title Computer-aided Prediction of Polyp Histology on White-Light Colonoscopy using Surface Pattern Analysis Type Journal Article
  Year 2019 Publication Endoscopy Abbreviated Journal END  
  Volume (up) 51 Issue 3 Pages 261-265  
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  Abstract Background and study aims: To evaluate a new computational histology prediction system based on colorectal polyp textural surface patterns using high definition white light images.
Patients and methods: Textural elements (textons) were characterized according to their contrast with respect to the surface, shape and number of bifurcations, assuming that dysplastic polyps are associated with highly contrasted, large tubular patterns with some degree of bifurcation. Computer-aided diagnosis (CAD) was compared with pathological diagnosis and the diagnosis by the endoscopists using Kudo and NICE classification.
Results: Images of 225 polyps were evaluated (142 dysplastic and 83 non-dysplastic). CAD system correctly classified 205 (91.1%) polyps, 131/142 (92.3%) dysplastic and 74/83 (89.2%) non-dysplastic. For the subgroup of 100 diminutive (<5 mm) polyps, CAD correctly classified 87 (87%) polyps, 43/50 (86%) dysplastic and 44/50 (88%) non-dysplastic. There were not statistically significant differences in polyp histology prediction based on CAD system and on endoscopist assessment.
Conclusion: A computer vision system based on the characterization of the polyp surface in the white light accurately predicts colorectal polyp histology.
 
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  Notes MV; 600.096; 600.119; 600.075 Approved no  
  Call Number Admin @ si @ SSB2019 Serial 3164  
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