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Author |
Aitor Alvarez-Gila; Joost Van de Weijer; Estibaliz Garrote |
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Title |
Adversarial Networks for Spatial Context-Aware Spectral Image Reconstruction from RGB |
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Conference Article |
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Year |
2017 |
Publication  |
1st International Workshop on Physics Based Vision meets Deep Learning |
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Hyperspectral signal reconstruction aims at recovering the original spectral input that produced a certain trichromatic (RGB) response from a capturing device or observer.
Given the heavily underconstrained, non-linear nature of the problem, traditional techniques leverage different statistical properties of the spectral signal in order to build informative priors from real world object reflectances for constructing such RGB to spectral signal mapping. However,
most of them treat each sample independently, and thus do not benefit from the contextual information that the spatial dimensions can provide. We pose hyperspectral natural image reconstruction as an image to image mapping learning problem, and apply a conditional generative adversarial framework to help capture spatial semantics. This is the first time Convolutional Neural Networks -and, particularly, Generative Adversarial Networks- are used to solve this task. Quantitative evaluation shows a Root Mean Squared Error (RMSE) drop of 44:7% and a Relative RMSE drop of 47:0% on the ICVL natural hyperspectral image dataset. |
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Venice; Italy; October 2017 |
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ICCV-PBDL |
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LAMP; 600.109; 600.106; 600.120 |
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no |
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Call Number |
Admin @ si @ AWG2017 |
Serial |
2969 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Single Snapshot 3D Head Pose Initialization for Tracking in Human Robot Interaction Scenario |
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Conference Article |
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Year |
2010 |
Publication |
1st International Workshop on Computer Vision for Human-Robot Interaction |
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32–39 |
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1st International Workshop on Computer Vision for Human-Robot Interaction, in conjunction with IEEE CVPR 2010 |
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This paper presents an automatic 3D head pose initialization scheme for a real-time face tracker with application to human-robot interaction. It has two main contributions. First, we propose an automatic 3D head pose and person specific face shape estimation, based on a 3D deformable model. The proposed approach serves to initialize our realtime 3D face tracker. What makes this contribution very attractive is that the initialization step can cope with faces
under arbitrary pose, so it is not limited only to near-frontal views. Second, the previous framework is used to develop an application in which the orientation of an AIBO’s camera can be controlled through the imitation of user’s head pose.
In our scenario, this application is used to build panoramic images from overlapping snapshots. Experiments on real videos confirm the robustness and usefulness of the proposed methods. |
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San Francisco; CA; USA; June 2010 |
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2160-7508 |
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978-1-4244-7029-7 |
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CVPRW |
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OR;MV |
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no |
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BCNPCL @ bcnpcl @ DoR2010a |
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1309 |
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Author |
Leonardo Galteri; Dena Bazazian; Lorenzo Seidenari; Marco Bertini; Andrew Bagdanov; Anguelos Nicolaou; Dimosthenis Karatzas; Alberto del Bimbo |
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Title |
Reading Text in the Wild from Compressed Images |
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Conference Article |
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Year |
2017 |
Publication |
1st International workshop on Egocentric Perception, Interaction and Computing |
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Reading text in the wild is gaining attention in the computer vision community. Images captured in the wild are almost always compressed to varying degrees, depending on application context, and this compression introduces artifacts
that distort image content into the captured images. In this paper we investigate the impact these compression artifacts have on text localization and recognition in the wild. We also propose a deep Convolutional Neural Network (CNN) that can eliminate text-specific compression artifacts and which leads to an improvement in text recognition. Experimental results on the ICDAR-Challenge4 dataset demonstrate that compression artifacts have a significant
impact on text localization and recognition and that our approach yields an improvement in both – especially at high compression rates. |
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Venice; Italy; October 2017 |
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ICCV - EPIC |
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Notes |
DAG; 600.084; 600.121 |
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no |
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Call Number |
Admin @ si @ GBS2017 |
Serial |
3006 |
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Author |
Alejandro Cartas; Mariella Dimiccoli; Petia Radeva |
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Title |
Batch-based activity recognition from egocentric photo-streams |
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Conference Article |
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Year |
2017 |
Publication |
1st International workshop on Egocentric Perception, Interaction and Computing |
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Activity recognition from long unstructured egocentric photo-streams has several applications in assistive technology such as health monitoring and frailty detection, just to name a few. However, one of its main technical challenges is to deal with the low frame rate of wearable photo-cameras, which causes abrupt appearance changes between consecutive frames. In consequence, important discriminatory low-level features from motion such as optical flow cannot be estimated. In this paper, we present a batch-driven approach for training a deep learning architecture that strongly rely on Long short-term units to tackle this problem. We propose two different implementations of the same approach that process a photo-stream sequence using batches of fixed size with the goal of capturing the temporal evolution of high-level features. The main difference between these implementations is that one explicitly models consecutive batches by overlapping them. Experimental results over a public dataset acquired by three users demonstrate the validity of the proposed architectures to exploit the temporal evolution of convolutional features over time without relying on event boundaries. |
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Venice; Italy; October 2017; |
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ICCV - EPIC |
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Notes |
MILAB; no menciona |
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no |
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Call Number |
Admin @ si @ CDR2017 |
Serial |
3023 |
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Author |
Dimosthenis Karatzas; Lluis Gomez; Marçal Rusiñol |
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Title |
The Robust Reading Competition Annotation and Evaluation Platform |
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Conference Article |
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Year |
2017 |
Publication |
1st International Workshop on Open Services and Tools for Document Analysis |
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The ICDAR Robust Reading Competition (RRC), initiated in 2003 and re-established in 2011, has become the defacto evaluation standard for the international community. Concurrent with its second incarnation in 2011, a continuous effort started to develop an online framework to facilitate the hosting and management of competitions. This short paper briefly outlines the Robust Reading Competition Annotation and Evaluation Platform, the backbone of the Robust Reading Competition, comprising a collection of tools and processes that aim to simplify the management and annotation
of data, and to provide online and offline performance evaluation and analysis services |
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Kyoto; Japan; November 2017 |
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ICDAR-OST |
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DAG; 600.084; 600.121; 600.129 |
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no |
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Call Number |
Admin @ si @ KGR2017 |
Serial |
3063 |
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Author |
Arnau Baro; Pau Riba; Alicia Fornes |
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Title |
A Starting Point for Handwritten Music Recognition |
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Conference Article |
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Year |
2018 |
Publication |
1st International Workshop on Reading Music Systems |
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5-6 |
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Optical Music Recognition; Long Short-Term Memory; Convolutional Neural Networks; MUSCIMA++; CVCMUSCIMA |
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In the last years, the interest in Optical Music Recognition (OMR) has reawakened, especially since the appearance of deep learning. However, there are very few works addressing handwritten scores. In this work we describe a full OMR pipeline for handwritten music scores by using Convolutional and Recurrent Neural Networks that could serve as a baseline for the research community. |
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Paris; France; September 2018 |
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WORMS |
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DAG; 600.097; 601.302; 601.330; 600.121 |
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no |
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Admin @ si @ BRF2018 |
Serial |
3223 |
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Author |
Lluis Gomez; Dimosthenis Karatzas |
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Title |
Scene Text Recognition: No Country for Old Men? |
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Conference Article |
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2014 |
Publication |
1st International Workshop on Robust Reading |
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IWRR |
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DAG; 600.077 |
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no |
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Admin @ si @ GoK2014c |
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2538 |
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Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
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Title |
Synthetic ground truth dataset to detect shadow cast by static objects in outdoor |
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Conference Article |
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2012 |
Publication |
1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications |
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art. 11 |
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In this paper, we propose a precise synthetic ground truth dataset to study the problem of detection of the shadows cast by static objects in outdoor environments during extended periods of time (days). For our dataset, we have created a virtual scenario using a rendering software. To increase the realism of the simulated environment, we have defined the scenario in a precise geographical location. In our dataset the sun is by far the main illumination source. The sun position during the simulation time takes into consideration factors related to the geographical location, such as the latitude, longitude, elevation above sea level, and precise image capturing day and time. In our simulation the camera remains fixed. The dataset consists of seven days of simulation, from 10:00am to 5:00pm. Images are captured every 10 seconds. The shadows' ground truth is automatically computed by the rendering software. |
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Capri, Italy |
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ACM |
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978-1-4503-1405-3 |
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VIGTA |
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OR;MV |
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no |
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Admin @ si @ ISR2012a |
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2037 |
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Author |
Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez |
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Title |
Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis |
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Conference Article |
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Year |
2014 |
Publication |
1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy |
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8899 |
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1-10 |
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Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps |
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In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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LNCS |
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0302-9743 |
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978-3-319-13409-3 |
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CARE |
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MV; IAM; 600.044; 600.047; 600.060; 600.075 |
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no |
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Admin @ si @ BGS2014b |
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2503 |
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Author |
Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika |
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Title |
Facial Expression Recognition based on Multi-view Observations with Application to Social Robotics |
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Conference Article |
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2014 |
Publication |
1st Workshop on Computer Vision for Affective Computing |
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1-8 |
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Human-robot interaction is a hot topic nowadays in the social robotics community. One crucial aspect is represented by the affective communication which comes encoded through the facial expressions. In this paper, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, view- and texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial
expression. |
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Singapore; November 2014 |
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ACCV |
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OR;MV |
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no |
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Admin @ si @ RBD2014 |
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2599 |
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Author |
D. Lloret; Joan Serrat; Antonio Lopez; Juan J. Villanueva |
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Motion-induced error correction in ultrasound imaging. |
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Miscellaneous |
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2002 |
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1st. International Symposium on 3D Data Processing Visualization and Transmission 3DPTV. |
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ADAS |
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ADAS @ adas @ LSL2002 |
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295 |
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Author |
Zhong Jin; Jing-Yu Yang; Zhen Lou |
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A luminance-conditional distribution model of skin color information |
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Miscellaneous |
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2005 |
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2005 Beijing International Conference on Imaging: Technology and Applications for the 21th Century, 280–281 |
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Beijing (China) |
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Admin @ si @ JYL2005 |
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628 |
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Author |
Francisco Javier Orozco; Jordi Gonzalez |
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Confidence Assessment on Eyelid and Eyebrow Expression Recognition |
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2008 |
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2008 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008) |
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Amsterdam (Holanda) |
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ISE |
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ISE @ ise @ OrG2008 |
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1111 |
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Author |
Jorge Bernal; Fernando Vilariño; F. Javier Sanchez; M. Arnold; Anarta Ghosh; Gerard Lacey |
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Experts vs Novices: Applying Eye-tracking Methodologies in Colonoscopy Video Screening for Polyp Search |
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Conference Article |
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2014 |
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2014 Symposium on Eye Tracking Research and Applications |
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223-226 |
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We present in this paper a novel study aiming at identifying the differences in visual search patterns between physicians of diverse levels of expertise during the screening of colonoscopy videos. Physicians were clustered into two groups -experts and novices- according to the number of procedures performed, and fixations were captured by an eye-tracker device during the task of polyp search in different video sequences. These fixations were integrated into heat maps, one for each cluster. The obtained maps were validated over a ground truth consisting of a mask of the polyp, and the comparison between experts and novices was performed by using metrics such as reaction time, dwelling time and energy concentration ratio. Experimental results show a statistically significant difference between experts and novices, and the obtained maps show to be a useful tool for the characterisation of the behaviour of each group. |
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USA; March 2014 |
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978-1-4503-2751-0 |
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ETRA |
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MV; 600.047; 600.060;SIAI |
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Admin @ si @ BVS2014 |
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2448 |
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Xavier Baro; Jordi Gonzalez; Junior Fabian; Miguel Angel Bautista; Marc Oliu; Hugo Jair Escalante; Isabelle Guyon; Sergio Escalera |
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ChaLearn Looking at People 2015 challenges: action spotting and cultural event recognition |
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2015 |
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2015 IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) |
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1-9 |
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Following previous series on Looking at People (LAP) challenges [6, 5, 4], ChaLearn ran two competitions to be presented at CVPR 2015: action/interaction spotting and cultural event recognition in RGB data. We ran a second round on human activity recognition on RGB data sequences. In terms of cultural event recognition, tens of categories have to be recognized. This involves scene understanding and human analysis. This paper summarizes the two performed challenges and obtained results. Details of the ChaLearn LAP competitions can be found at http://gesture.chalearn.org/. |
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Boston; EEUU; June 2015 |
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CVPRW |
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HuPBA;MV |
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2652 |
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