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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 | ||||
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 | 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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Author | Cristina Sanchez Montes; F. Javier Sanchez; Cristina Rodriguez de Miguel; Henry Cordova; Jorge Bernal; Maria Lopez Ceron; Josep Llach; Gloria Fernandez Esparrach | ||||
Title | Histological Prediction Of Colonic Polyps By Computer Vision. Preliminary Results | Type | Conference Article | ||
Year | 2017 | Publication | 25th United European Gastroenterology Week | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | polyps; histology; computer vision | ||||
Abstract | during colonoscopy, clinicians perform visual inspection of the polyps to predict histology. Kudo’s pit pattern classification is one of the most commonly used for optical diagnosis. These surface patterns present a contrast with respect to their neighboring regions and they can be considered as bright regions in the image that can attract the attention of computational methods. | ||||
Address | Barcelona; October 2017 | ||||
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Area | Expedition | Conference | ESGE | ||
Notes | MV; no menciona | Approved | no | ||
Call Number | Admin @ si @ SSR2017 | Serial | 2979 | ||
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Author | Cristina Palmero; Oleg V Komogortsev; Sergio Escalera; Sachin S Talathi | ||||
Title | Multi-Rate Sensor Fusion for Unconstrained Near-Eye Gaze Estimation | Type | Conference Article | ||
Year | 2023 | Publication | Proceedings of the 2023 Symposium on Eye Tracking Research and Applications | Abbreviated Journal | |
Volume | Issue | Pages | 1-8 | ||
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Abstract | The power requirements of video-oculography systems can be prohibitive for high-speed operation on portable devices. Recently, low-power alternatives such as photosensors have been evaluated, providing gaze estimates at high frequency with a trade-off in accuracy and robustness. Potentially, an approach combining slow/high-fidelity and fast/low-fidelity sensors should be able to exploit their complementarity to track fast eye motion accurately and robustly. To foster research on this topic, we introduce OpenSFEDS, a near-eye gaze estimation dataset containing approximately 2M synthetic camera-photosensor image pairs sampled at 500 Hz under varied appearance and camera position. We also formulate the task of sensor fusion for gaze estimation, proposing a deep learning framework consisting in appearance-based encoding and temporal eye-state dynamics. We evaluate several single- and multi-rate fusion baselines on OpenSFEDS, achieving 8.7% error decrease when tracking fast eye movements with a multi-rate approach vs. a gaze forecasting approach operating with a low-speed sensor alone. | ||||
Address | Tubingen; Germany; May 2023 | ||||
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Area | Expedition | Conference | ETRA | ||
Notes | HUPBA | Approved | no | ||
Call Number | Admin @ si @ PKE2023 | Serial | 3923 | ||
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Author | Cristina Palmero; Jordi Esquirol; Vanessa Bayo; Miquel Angel Cos; Pouya Ahmadmonfared; Joan Salabert; David Sanchez; Sergio Escalera | ||||
Title | Automatic Sleep System Recommendation by Multi-modal RBG-Depth-Pressure Anthropometric Analysis | Type | Journal Article | ||
Year | 2017 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
Volume | 122 | Issue | 2 | Pages | 212–227 |
Keywords | Sleep system recommendation; RGB-Depth data Pressure imaging; Anthropometric landmark extraction; Multi-part human body segmentation | ||||
Abstract | This paper presents a novel system for automatic sleep system recommendation using RGB, depth and pressure information. It consists of a validated clinical knowledge-based model that, along with a set of prescription variables extracted automatically, obtains a personalized bed design recommendation. The automatic process starts by performing multi-part human body RGB-D segmentation combining GrabCut, 3D Shape Context descriptor and Thin Plate Splines, to then extract a set of anthropometric landmark points by applying orthogonal plates to the segmented human body. The extracted variables are introduced to the computerized clinical model to calculate body circumferences, weight, morphotype and Body Mass Index categorization. Furthermore, pressure image analysis is performed to extract pressure values and at-risk points, which are also introduced to the model to eventually obtain the final prescription of mattress, topper, and pillow. We validate the complete system in a set of 200 subjects, showing accurate category classification and high correlation results with respect to manual measures. | ||||
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Notes | HuPBA;MILAB; 303.100 | Approved | no | ||
Call Number | Admin @ si @ PEB2017 | Serial | 2765 | ||
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Author | Cristina Palmero; Javier Selva; Sorina Smeureanu; Julio C. S. Jacques Junior; Albert Clapes; Alexa Mosegui; Zejian Zhang; David Gallardo; Georgina Guilera; David Leiva; Sergio Escalera | ||||
Title | Context-Aware Personality Inference in Dyadic Scenarios: Introducing the UDIVA Dataset | Type | Conference Article | ||
Year | 2021 | Publication | IEEE Winter Conference on Applications of Computer Vision | Abbreviated Journal | |
Volume | Issue | Pages | 1-12 | ||
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Abstract | This paper introduces UDIVA, a new non-acted dataset of face-to-face dyadic interactions, where interlocutors perform competitive and collaborative tasks with different behavior elicitation and cognitive workload. The dataset consists of 90.5 hours of dyadic interactions among 147 participants distributed in 188 sessions, recorded using multiple audiovisual and physiological sensors. Currently, it includes sociodemographic, self- and peer-reported personality, internal state, and relationship profiling from participants. As an initial analysis on UDIVA, we propose a
transformer-based method for self-reported personality inference in dyadic scenarios, which uses audiovisual data and different sources of context from both interlocutors to regress a target person’s personality traits. Preliminary results from an incremental study show consistent improvements when using all available context information. |
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Address | Virtual; January 2021 | ||||
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Area | Expedition | Conference | WACV | ||
Notes | HUPBA | Approved | no | ||
Call Number | Admin @ si @ PSS2021 | Serial | 3532 | ||
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Author | Cristina Palmero; Javier Selva; Mohammad Ali Bagheri; Sergio Escalera | ||||
Title | Recurrent CNN for 3D Gaze Estimation using Appearance and Shape Cues | Type | Conference Article | ||
Year | 2018 | Publication | 29th British Machine Vision Conference | Abbreviated Journal | |
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Abstract | Gaze behavior is an important non-verbal cue in social signal processing and humancomputer interaction. In this paper, we tackle the problem of person- and head poseindependent 3D gaze estimation from remote cameras, using a multi-modal recurrent convolutional neural network (CNN). We propose to combine face, eyes region, and face landmarks as individual streams in a CNN to estimate gaze in still images. Then, we exploit the dynamic nature of gaze by feeding the learned features of all the frames in a sequence to a many-to-one recurrent module that predicts the 3D gaze vector of the last frame. Our multi-modal static solution is evaluated on a wide range of head poses and gaze directions, achieving a significant improvement of 14.6% over the state of the art on
EYEDIAP dataset, further improved by 4% when the temporal modality is included. |
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Address | Newcastle; UK; September 2018 | ||||
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Area | Expedition | Conference | BMVC | ||
Notes | HUPBA; no proj | Approved | no | ||
Call Number | Admin @ si @ PSB2018 | Serial | 3208 | ||
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Author | Cristina Palmero; Albert Clapes; Chris Bahnsen; Andreas Møgelmose; Thomas B. Moeslund; Sergio Escalera | ||||
Title | Multi-modal RGB-Depth-Thermal Human Body Segmentation | Type | Journal Article | ||
Year | 2016 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
Volume | 118 | Issue | 2 | Pages | 217-239 |
Keywords | Human body segmentation; RGB ; Depth Thermal | ||||
Abstract | This work addresses the problem of human body segmentation from multi-modal visual cues as a first stage of automatic human behavior analysis. We propose a novel RGB–depth–thermal dataset along with a multi-modal segmentation baseline. The several modalities are registered using a calibration device and a registration algorithm. Our baseline extracts regions of interest using background subtraction, defines a partitioning of the foreground regions into cells, computes a set of image features on those cells using different state-of-the-art feature extractions, and models the distribution of the descriptors per cell using probabilistic models. A supervised learning algorithm then fuses the output likelihoods over cells in a stacked feature vector representation. The baseline, using Gaussian mixture models for the probabilistic modeling and Random Forest for the stacked learning, is superior to other state-of-the-art methods, obtaining an overlap above 75 % on the novel dataset when compared to the manually annotated ground-truth of human segmentations. | ||||
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Publisher | Springer US | Place of Publication | Editor | ||
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Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ PCB2016 | Serial | 2767 | ||
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Author | Cristina Cañero; Petia Radeva; Ricardo Toledo; Juan J. Villanueva; J. Mauri | ||||
Title | 3D Curve Reconstruction by Biplane Snakes. | Type | Conference Article | ||
Year | 2000 | Publication | 15 th International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | 4 | Issue | Pages | 563-566 | |
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Address | Barcelona. | ||||
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Area | Expedition | Conference | ICPR | ||
Notes | MILAB;ADAS | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ CRT2000 | Serial | 238 | ||
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Author | Cristina Cañero; Petia Radeva; Oriol Pujol; Ricardo Toledo; Debora Gil; J. Saludes; Juan J. Villanueva; B. Garcia del Blanco; J. Mauri; Eduard Fernandez-Nofrerias; J.A. Gomez-Hospital; E. Iraculis; J. Comin; C. Quiles; F. Jara; A. Cequier; E.Esplugas | ||||
Title | Three-dimensional reconstruction and quantification of the coronary tree using intravascular ultrasound images | Type | Conference Article | ||
Year | 1999 | Publication | Proceedings of International Conference on Computer in Cardiology (CIC´99) | Abbreviated Journal | |
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Abstract | In this paper we propose a new Computer Vision technique to reconstruct the vascular wall in space using a deformable model-based technique and compounding methods, based in biplane angiography and intravascular ultrasound data jicsion. It is also proposed a generalpurpose three-dimensional guided interpolation method. The three dimensional centerline of the vessel is reconstructed from geometrically corrected biplane angiographies using automatic segmentation methods and snakes. The IVUS image planes are located in the threedimensional space and correctly oriented. A led interpolation method based in B-SurJaces and snakes isused to fill the gaps among image planes | ||||
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Area | Expedition | Conference | CINC99 | ||
Notes | MILAB;RV;IAM;ADAS;HuPBA | Approved | no | ||
Call Number | IAM @ iam @ CRP1999b | Serial | 1492 | ||
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Author | Cristina Cañero; Petia Radeva; Oriol Pujol; Ricardo Toledo; Debora Gil; J. Saludes; Juan J. Villanueva; B. Garcia del Blanco; J. Mauri; E. Fernandez-Nofrerias; J.A. Gomez-Hospital; E. Iraculis; J. Comin; C. Quiles; F. Jara; A. Cequier; E. Esplugas | ||||
Title | Optimal Stent Implantation: Three-dimensional Evaluation of the Mutual Position of Stent and Vessel via Intracoronary Ecography | Type | Conference Article | ||
Year | 1999 | Publication | Proceedings of International Conference on Computer in Cardiology (CIC´99) | Abbreviated Journal | |
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Abstract | We present a new automatic technique to visualize and quantify the mutual position between the stent and the vessel wall by considering their three-dimensional reconstruction. Two deformable generalized cylinders adapt to the image features in all IVUS planes corresponding to the vessel wall and the stent in order to reconstruct the boundaries of the stent and the vessel in space. The image features that characterize the stent and the vessel wall are determined in terms of edge and ridge image detectors taking into account the gray level of the image pixels. We show that the 30 reconstruction by deformable cylinders is accurate and robust due to the spatial data coherence in the considered volumetric IVUS image. The main clinic utility of the stent and vessel reconstruction by deformable’ cylinders consists of its possibility to visualize and to assess the optimal stent introduction. | ||||
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Notes | MILAB; RV; IAM; ADAS; HuPBA | Approved | no | ||
Call Number | IAM @ iam @ CRP1999a | Serial | 1491 | ||
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Author | Cristina Cañero; Petia Radeva; M. Gomez; J. Mauri; E. Fernandez-Nofrerias; Oriol Rodriguez-Leor; C. Julia | ||||
Title | Modelo experimental para la reconstruccion tridimensional de las arterias coronarias a partir de imagenes de coronariografia | Type | Journal | ||
Year | 2002 | Publication | Abbreviated Journal | ||
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Address | Madrid | ||||
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Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ GMF2002e | Serial | 434 | ||
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Author | Cristina Cañero; Petia Radeva | ||||
Title | Predictive (un)distortion model for 3D reconstruction purpouses | Type | Report | ||
Year | 2002 | Publication | CVC Technical Report # 61 | Abbreviated Journal | |
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Address | CVC (UAB) | ||||
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Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ CaR2002 | Serial | 327 | ||
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Author | Cristina Cañero; Petia Radeva | ||||
Title | Vesselness enhancement diffusion | Type | Journal Article | ||
Year | 2003 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 24 | Issue | 16 | Pages | 3141–3151 |
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Abstract | IF: 0.809 | ||||
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Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ CaR2003 | Serial | 371 | ||
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Author | Cristina Cañero; Nikolaos Thomos; George A. Triantafyllid; George C. Litos; Michael G. Strintzis | ||||
Title | Mobile Tele-echography: User Interface Design | Type | Journal | ||
Year | 2005 | Publication | IEEE Transactions on Information Technology in Biomedicine, 9(1):44–49 (IF: 1.376) | Abbreviated Journal | |
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Notes | Approved | no | |||
Call Number | Admin @ si @ CTT2005 | Serial | 537 | ||
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Author | Cristina Cañero; Fernando Vilariño; Petia Radeva | ||||
Title | Predictive (un) distortion model and 3D Reconstruction by Biplane Snakes | Type | Journal | ||
Year | 2002 | Publication | IEEE Transactions on Medical Imaging (IF: 2.911) | Abbreviated Journal | |
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Notes | MILAB;SIAI | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ CVR2002 | Serial | 269 | ||
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