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Author |
Fernando Vilariño; Gerard Lacey; Jiang Zhou; Hugh Mulcahy; Stephen Patchett |
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Title  |
Automatic Labeling of Colonoscopy Video for Cancer Detection |
Type |
Conference Article |
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Year |
2007 |
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In Proc. berian Conference, IbPRIA |
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290-297 |
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800 |
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MV;SIAI |
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no |
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Call Number |
fernando @ fernando @ |
Serial |
2431 |
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Author |
Carles Fernandez; Jordi Gonzalez; Xavier Roca |
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Title |
Automatic Learning of Background Semantics in Generic Surveilled Scenes |
Type |
Conference Article |
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Year |
2010 |
Publication |
11th European Conference on Computer Vision |
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Volume |
6313 |
Issue |
II |
Pages |
678–692 |
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Abstract |
Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analysis techniques statistically infer semantics in locations where motion occurs, and such inferences are typically limited to abnormality. Thus, it is interesting to design contributions that automatically categorize more specific semantic regions. State-of-the-art approaches for unsupervised scene labeling exploit trajectory data to segment areas like sources, sinks, or waiting zones. Our method, in addition, incorporates scene-independent knowledge to assign more meaningful labels like crosswalks, sidewalks, or parking spaces. First, a spatiotemporal scene model is obtained from trajectory analysis. Subsequently, a so-called GI-MRF inference process reinforces spatial coherence, and incorporates taxonomy-guided smoothness constraints. Our method achieves automatic and effective labeling of conceptual regions in urban scenarios, and is robust to tracking errors. Experimental validation on 5 surveillance databases has been conducted to assess the generality and accuracy of the segmentations. The resulting scene models are used for model-based behavior analysis. |
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Crete (Greece) |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-15551-2 |
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ECCV |
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ISE |
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no |
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Call Number |
ISE @ ise @ FGR2010 |
Serial |
1439 |
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Author |
Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva |
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Title |
Automatic Non-Rigid Temporal Alignment of IVUS Sequences |
Type |
Conference Article |
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Year |
2012 |
Publication |
15th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Volume |
1 |
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Pages |
642-650 |
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Abstract |
Clinical studies on atherosclerosis regression/progression performed by Intravascular Ultrasound analysis require the alignment of pullbacks of the same patient before and after clinical interventions. In this paper, a methodology for the automatic alignment of IVUS sequences based on the Dynamic Time Warping technique is proposed. The method is adapted to the specific IVUS alignment task by applying the non-rigid alignment technique to multidimensional morphological signals, and by introducing a sliding window approach together with a regularization term. To show the effectiveness of our method, an extensive validation is performed both on synthetic data and in-vivo IVUS sequences. The proposed method is robust to stent deployment and post dilation surgery and reaches an alignment error of approximately 0.7 mm for in-vivo data, which is comparable to the inter-observer variability. |
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Nice, France |
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Springer-Verlag Berlin, Heidelberg |
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978-3-642-33414-6 |
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MICCAI |
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MILAB |
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no |
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Call Number |
Admin @ si @ ABC2012 |
Serial |
2168 |
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Author |
Mario Rojas; David Masip; A. Todorov; Jordi Vitria |
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Title |
Automatic Point-based Facial Trait Judgments Evaluation |
Type |
Conference Article |
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Year |
2010 |
Publication |
23rd IEEE Conference on Computer Vision and Pattern Recognition |
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Pages |
2715–2720 |
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Abstract |
Humans constantly evaluate the personalities of other people using their faces. Facial trait judgments have been studied in the psychological field, and have been determined to influence important social outcomes of our lives, such as elections outcomes and social relationships. Recent work on textual descriptions of faces has shown that trait judgments are highly correlated. Further, behavioral studies suggest that two orthogonal dimensions, valence and dominance, can describe the basis of the human judgments from faces. In this paper, we used a corpus of behavioral data of judgments on different trait dimensions to automatically learn a trait predictor from facial pixel images. We study whether trait evaluations performed by humans can be learned using machine learning classifiers, and used later in automatic evaluations of new facial images. The experiments performed using local point-based descriptors show promising results in the evaluation of the main traits. |
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San Francisco CA, USA |
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ISSN |
1063-6919 |
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978-1-4244-6984-0 |
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Conference |
CVPR |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ RMT2010 |
Serial |
1282 |
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Author |
Mariona Caros; Maite Garolera; Petia Radeva; Xavier Giro |
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Title |
Automatic Reminiscence Therapy for Dementia |
Type |
Conference Article |
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Year |
2020 |
Publication |
10th ACM International Conference on Multimedia Retrieval |
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Volume |
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Pages |
383-387 |
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Abstract |
With people living longer than ever, the number of cases with dementia such as Alzheimer's disease increases steadily. It affects more than 46 million people worldwide, and it is estimated that in 2050 more than 100 million will be affected. While there are not effective treatments for these terminal diseases, therapies such as reminiscence, that stimulate memories from the past are recommended. Currently, reminiscence therapy takes place in care homes and is guided by a therapist or a carer. In this work, we present an AI-based solution to automatize the reminiscence therapy, which consists in a dialogue system that uses photos as input to generate questions. We run a usability case study with patients diagnosed of mild cognitive impairment that shows they found the system very entertaining and challenging. Overall, this paper presents how reminiscence therapy can be automatized by using machine learning, and deployed to smartphones and laptops, making the therapy more accessible to every person affected by dementia. |
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Virtual; October 2020 |
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ICRM |
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no |
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Call Number |
Admin @ si @ CGR2020 |
Serial |
3529 |
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Author |
Debora Gil; Petia Radeva; Jordi Saludes; J. Mauri |
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Title |
Automatic Segmentation of Artery Wall in Coronary IVUS Images: A Probabilistic Approach |
Type |
Conference Article |
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Year |
2000 |
Publication |
International Conference on Pattern Recognition |
Abbreviated Journal |
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Volume |
4 |
Issue |
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Pages |
352-355 |
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Abstract |
Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results. |
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Notes |
IAM;MILAB |
Approved |
no |
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Call Number |
IAM @ iam @ GRS2000a |
Serial |
1537 |
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Author |
Debora Gil; Petia Radeva; Jordi Saludes; J. Mauri |
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Title |
Automatic Segmentation of Artery Wall in Coronary IVUS Images: a Probabilistic Approach |
Type |
Conference Article |
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Year |
2000 |
Publication |
Proceedings of CIC’2000 |
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Abstract |
Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results. |
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Cambridge, Massachussets |
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CIC |
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IAM;MILAB |
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no |
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Call Number |
IAM @ iam @ GRS2000 |
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1538 |
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Author |
David Aldavert; Marçal Rusiñol; Ricardo Toledo |
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Title |
Automatic Static/Variable Content Separation in Administrative Document Images |
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Conference Article |
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Year |
2017 |
Publication |
14th International Conference on Document Analysis and Recognition |
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In this paper we present an automatic method for separating static and variable content from administrative document images. An alignment approach is able to unsupervisedly build probabilistic templates from a set of examples of the same document kind. Such templates define which is the likelihood of every pixel of being either static or variable content. In the extraction step, the same alignment technique is used to match
an incoming image with the template and to locate the positions where variable fields appear. We validate our approach on the public NIST Structured Tax Forms Dataset. |
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Kyoto; Japan; November 2017 |
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ICDAR |
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DAG; 600.084; 600.121 |
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no |
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Call Number |
Admin @ si @ ART2017 |
Serial |
3001 |
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Author |
Marçal Rusiñol; Lluis Gomez; A. Landman; M. Silva Constenla; Dimosthenis Karatzas |
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Title |
Automatic Structured Text Reading for License Plates and Utility Meters |
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Conference Article |
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Year |
2019 |
Publication |
BMVC Workshop on Visual Artificial Intelligence and Entrepreneurship |
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Reading text in images has attracted interest from computer vision researchers for
many years. Our technology focuses on the extraction of structured text – such as serial
numbers, machine readings, product codes, etc. – so that it is able to center its attention just on the relevant textual elements. It is conceived to work in an end-to-end fashion, bypassing any explicit text segmentation stage. In this paper we present two different industrial use cases where we have applied our automatic structured text reading technology. In the first one, we demonstrate an outstanding performance when reading license plates compared to the current state of the art. In the second one, we present results on our solution for reading utility meters. The technology is commercialized by a recently created spin-off company, and both solutions are at different stages of integration with final clients. |
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Cardiff; UK; September 2019 |
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BMVC-VAIE19 |
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Notes |
DAG; 600.129 |
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no |
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Call Number |
Admin @ si @ RGL2019 |
Serial |
3283 |
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Author |
Laura Igual; Antonio Hernandez; Sergio Escalera; Miguel Reyes; Josep Moya; Joan Carles Soliva; Jordi Faquet; Oscar Vilarroya; Petia Radeva |
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Title |
Automatic Techniques for Studying Attention-Deficit/Hyperactivity Disorder |
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Conference Article |
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2011 |
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Jornada TIC Salut Girona |
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TICGI |
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MILAB;HuPBA |
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no |
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Call Number |
Admin @ si @ IHE2011 |
Serial |
1755 |
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Author |
Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier |
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Title |
Automatic text localisation in scanned comic books |
Type |
Conference Article |
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Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
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814-819 |
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Keywords |
Text localization; comics; text/graphic separation; complex background; unstructured document |
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Abstract |
Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent document understanding enable direct content-based search as opposed to metadata only search (e.g. album title or author name). Few studies have been done in this direction. In this work we detail a novel approach for the automatic text localization in scanned comics book pages, an essential step towards a fully automatic comics book understanding. We focus on speech text as it is semantically important and represents the majority of the text present in comics. The approach is compared with existing methods of text localization found in the literature and results are presented. |
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Barcelona; February 2013 |
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VISAPP |
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DAG; CIC; 600.056 |
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no |
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Admin @ si @ RKW2013b |
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2261 |
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Author |
Antonio Hernandez; Carlos Primo; Sergio Escalera |
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Title |
Automatic user interaction correction via Multi-label Graph cuts |
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Conference Article |
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2011 |
Publication |
In ICCV 2011 1st IEEE International Workshop on Human Interaction in Computer Vision HICV |
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1276-1281 |
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Most applications in image segmentation requires from user interaction in order to achieve accurate results. However, user wants to achieve the desired segmentation accuracy reducing effort of manual labelling. In this work, we extend standard multi-label α-expansion Graph Cut algorithm so that it analyzes the interaction of the user in order to modify the object model and improve final segmentation of objects. The approach is inspired in the fact that fast user interactions may introduce some pixel errors confusing object and background. Our results with different degrees of user interaction and input errors show high performance of the proposed approach on a multi-label human limb segmentation problem compared with classical α-expansion algorithm. |
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978-1-4673-0062-9 |
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HICV |
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MILAB; HuPBA |
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no |
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Call Number |
Admin @ si @ HPE2011 |
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1892 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
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Title |
Automatic Verification of Properly Signed Multi-page Document Images |
Type |
Conference Article |
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Year |
2015 |
Publication |
Proceedings of the Eleventh International Symposium on Visual Computing |
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9475 |
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327-336 |
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Document Image; Manual Inspection; Signature Verification; Rejection Criterion; Document Flow |
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Abstract |
In this paper we present an industrial application for the automatic screening of incoming multi-page documents in a banking workflow aimed at determining whether these documents are properly signed or not. The proposed method is divided in three main steps. First individual pages are classified in order to identify the pages that should contain a signature. In a second step, we segment within those key pages the location where the signatures should appear. The last step checks whether the signatures are present or not. Our method is tested in a real large-scale environment and we report the results when checking two different types of real multi-page contracts, having in total more than 14,500 pages. |
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Las Vegas, Nevada, USA; December 2015 |
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LNCS |
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9475 |
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ISVC |
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DAG; 600.077 |
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no |
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Admin @ si @ |
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3189 |
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Author |
Antonio Hernandez; Carlo Gatta; Petia Radeva; Laura Igual; R. Letaz; Sergio Escalera |
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Title |
Automatic Vessel Segmentation For Angiography and CT Registration |
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Conference Article |
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2010 |
Publication |
Medical Image Computing in Catalunya: Graduate Student Workshop |
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Volume |
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Issue |
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Pages |
1–2 |
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Keywords |
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Abstract |
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Address |
Girona |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
MICCAT |
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Notes |
MILAB;HUPBA |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ HGR2010 |
Serial |
1474 |
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| Permanent link to this record |
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Author |
A. Pujol; Juan J. Villanueva; H. Wechsler |
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Title |
Automatic View Based Caricaturing. |
Type |
Conference Article |
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Year |
2000 |
Publication |
15 th International Conference on Pattern Recognition |
Abbreviated Journal |
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Volume |
1 |
Issue |
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Pages |
1072-1075 |
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Keywords |
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Abstract |
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Address |
Barcelona. |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
ICPR |
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Notes |
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Approved |
no |
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Call Number |
ISE @ ise @ PVW2000 |
Serial |
227 |
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| Permanent link to this record |
