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Egils Avots; M. Daneshmanda; Andres Traumann; Sergio Escalera; G. Anbarjafaria |
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Title |
Automatic garment retexturing based on infrared information |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2016 |
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Computers & Graphics |
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CG |
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59 |
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28-38 |
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Garment Retexturing; Texture Mapping; Infrared Images; RGB-D Acquisition Devices; Shading |
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This paper introduces a new automatic technique for garment retexturing using a single static image along with the depth and infrared information obtained using the Microsoft Kinect II as the RGB-D acquisition device. First, the garment is segmented out from the image using either the Breadth-First Search algorithm or the semi-automatic procedure provided by the GrabCut method. Then texture domain coordinates are computed for each pixel belonging to the garment using normalised 3D information. Afterwards, shading is applied to the new colours from the texture image. As the main contribution of the proposed method, the latter information is obtained based on extracting a linear map transforming the colour present on the infrared image to that of the RGB colour channels. One of the most important impacts of this strategy is that the resulting retexturing algorithm is colour-, pattern- and lighting-invariant. The experimental results show that it can be used to produce realistic representations, which is substantiated through implementing it under various experimentation scenarios, involving varying lighting intensities and directions. Successful results are accomplished also on video sequences, as well as on images of subjects taking different poses. Based on the Mean Opinion Score analysis conducted on many randomly chosen users, it has been shown to produce more realistic-looking results compared to the existing state-of-the-art methods suggested in the literature. From a wide perspective, the proposed method can be used for retexturing all sorts of segmented surfaces, although the focus of this study is on garment retexturing, and the investigation of the configurations is steered accordingly, since the experiments target an application in the context of virtual fitting rooms. |
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Admin @ si @ ADT2016 |
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2759 |
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Katerine Diaz; Aura Hernandez-Sabate; Antonio Lopez |
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A reduced feature set for driver head pose estimation |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2016 |
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Applied Soft Computing |
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ASOC |
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45 |
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98-107 |
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Head pose estimation; driving performance evaluation; subspace based methods; linear regression |
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Evaluation of driving performance is of utmost importance in order to reduce road accident rate. Since driving ability includes visual-spatial and operational attention, among others, head pose estimation of the driver is a crucial indicator of driving performance. This paper proposes a new automatic method for coarse and fine head's yaw angle estimation of the driver. We rely on a set of geometric features computed from just three representative facial keypoints, namely the center of the eyes and the nose tip. With these geometric features, our method combines two manifold embedding methods and a linear regression one. In addition, the method has a confidence mechanism to decide if the classification of a sample is not reliable. The approach has been tested using the CMU-PIE dataset and our own driver dataset. Despite the very few facial keypoints required, the results are comparable to the state-of-the-art techniques. The low computational cost of the method and its robustness makes feasible to integrate it in massive consume devices as a real time application. |
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ADAS; 600.085; 600.076; |
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Admin @ si @ DHL2016 |
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2760 |
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Sergio Escalera; Vassilis Athitsos; Isabelle Guyon |
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Challenges in multimodal gesture recognition |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2016 |
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Journal of Machine Learning Research |
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JMLR |
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17 |
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1-54 |
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Gesture Recognition; Time Series Analysis; Multimodal Data Analysis; Computer Vision; Pattern Recognition; Wearable sensors; Infrared Cameras; KinectTM |
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This paper surveys the state of the art on multimodal gesture recognition and introduces the JMLR special topic on gesture recognition 2011-2015. We began right at the start of the KinectTMrevolution when inexpensive infrared cameras providing image depth recordings became available. We published papers using this technology and other more conventional methods, including regular video cameras, to record data, thus providing a good overview of uses of machine learning and computer vision using multimodal data in this area of application. Notably, we organized a series of challenges and made available several datasets we recorded for that purpose, including tens of thousands
of videos, which are available to conduct further research. We also overview recent state of the art works on gesture recognition based on a proposed taxonomy for gesture recognition, discussing challenges and future lines of research. |
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Zhuowen Tu |
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HuPBA;MILAB; |
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Admin @ si @ EAG2016 |
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2764 |
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Cristina Palmero; Jordi Esquirol; Vanessa Bayo; Miquel Angel Cos; Pouya Ahmadmonfared; Joan Salabert; David Sanchez; Sergio Escalera |
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Title |
Automatic Sleep System Recommendation by Multi-modal RBG-Depth-Pressure Anthropometric Analysis |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2017 |
Publication |
International Journal of Computer Vision |
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IJCV |
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122 |
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2 |
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212–227 |
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Sleep system recommendation; RGB-Depth data Pressure imaging; Anthropometric landmark extraction; Multi-part human body segmentation |
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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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HuPBA;MILAB; 303.100 |
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Admin @ si @ PEB2017 |
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2765 |
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Pejman Rasti; Salma Samiei; Mary Agoyi; Sergio Escalera; Gholamreza Anbarjafari |
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Title |
Robust non-blind color video watermarking using QR decomposition and entropy analysis |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2016 |
Publication |
Journal of Visual Communication and Image Representation |
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JVCIR |
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38 |
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838-847 |
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Video watermarking; QR decomposition; Discrete Wavelet Transformation; Chirp Z-transform; Singular value decomposition; Orthogonal–triangular decomposition |
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Issues such as content identification, document and image security, audience measurement, ownership and copyright among others can be settled by the use of digital watermarking. Many recent video watermarking methods show drops in visual quality of the sequences. The present work addresses the aforementioned issue by introducing a robust and imperceptible non-blind color video frame watermarking algorithm. The method divides frames into moving and non-moving parts. The non-moving part of each color channel is processed separately using a block-based watermarking scheme. Blocks with an entropy lower than the average entropy of all blocks are subject to a further process for embedding the watermark image. Finally a watermarked frame is generated by adding moving parts to it. Several signal processing attacks are applied to each watermarked frame in order to perform experiments and are compared with some recent algorithms. Experimental results show that the proposed scheme is imperceptible and robust against common signal processing attacks. |
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HuPBA;MILAB; |
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Admin @ si @RSA2016 |
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2766 |
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Cristina Palmero; Albert Clapes; Chris Bahnsen; Andreas Møgelmose; Thomas B. Moeslund; Sergio Escalera |
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Title |
Multi-modal RGB-Depth-Thermal Human Body Segmentation |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2016 |
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International Journal of Computer Vision |
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IJCV |
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118 |
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2 |
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217-239 |
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Human body segmentation; RGB ; Depth Thermal |
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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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Springer US |
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HuPBA;MILAB; |
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Admin @ si @ PCB2016 |
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2767 |
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Author |
Gerard Canal; Sergio Escalera; Cecilio Angulo |
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Title |
A Real-time Human-Robot Interaction system based on gestures for assistive scenarios |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2016 |
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Computer Vision and Image Understanding |
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CVIU |
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149 |
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65-77 |
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Gesture recognition; Human Robot Interaction; Dynamic Time Warping; Pointing location estimation |
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Natural and intuitive human interaction with robotic systems is a key point to develop robots assisting people in an easy and effective way. In this paper, a Human Robot Interaction (HRI) system able to recognize gestures usually employed in human non-verbal communication is introduced, and an in-depth study of its usability is performed. The system deals with dynamic gestures such as waving or nodding which are recognized using a Dynamic Time Warping approach based on gesture specific features computed from depth maps. A static gesture consisting in pointing at an object is also recognized. The pointed location is then estimated in order to detect candidate objects the user may refer to. When the pointed object is unclear for the robot, a disambiguation procedure by means of either a verbal or gestural dialogue is performed. This skill would lead to the robot picking an object in behalf of the user, which could present difficulties to do it by itself. The overall system — which is composed by a NAO and Wifibot robots, a KinectTM v2 sensor and two laptops — is firstly evaluated in a structured lab setup. Then, a broad set of user tests has been completed, which allows to assess correct performance in terms of recognition rates, easiness of use and response times. |
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Elsevier B.V. |
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HuPBA;MILAB; |
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Admin @ si @ CEA2016 |
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2768 |
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Debora Gil; Sergio Vera; Agnes Borras; Albert Andaluz; Miguel Angel Gonzalez Ballester |
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Title |
Anatomical Medial Surfaces with Efficient Resolution of Branches Singularities |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2017 |
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Medical Image Analysis |
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MIA |
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35 |
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390-402 |
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Medial Representations; Shape Recognition; Medial Branching Stability ; Singular Points |
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Medial surfaces are powerful tools for shape description, but their use has been limited due to the sensibility existing methods to branching artifacts. Medial branching artifacts are associated to perturbations of the object boundary rather than to geometric features. Such instability is a main obstacle for a condent application in shape recognition and description. Medial branches correspond to singularities of the medial surface and, thus, they are problematic for existing morphological and energy-based algorithms. In this paper, we use algebraic geometry concepts in an energy-based approach to compute a medial surface presenting a stable branching topology. We also present an ecient GPU-CPU implementation using standard image processing tools. We show the method computational eciency and quality on a custom made synthetic database. Finally, we present some results on a medical imaging application for localization of abdominal pathologies. |
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Elsevier B.V. |
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IAM; 600.060; 600.096; 600.075; 600.145 |
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Admin @ si @ GVB2017 |
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2775 |
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Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Growing Algorithm for Intersection Detection (GRAID) in branching patterns |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2015 |
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Machine Vision and Applications |
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MVAP |
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26 |
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2 |
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387-400 |
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Bifurcation ; Crossroad; Intersection ;Retina ; Vessel |
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Analysis of branching structures represents a very important task in fields such as medical diagnosis, road detection or biometrics. Detecting intersection landmarks Becomes crucial when capturing the structure of a branching pattern. We present a very simple geometrical model to describe intersections in branching structures based on two conditions: Bounded Tangency condition (BT) and Shortest Branch (SB) condition. The proposed model precisely sets a geometrical characterization of intersections and allows us to introduce a new unsupervised operator for intersection extraction. We propose an implementation that handles the consequences of digital domain operation that,unlike existing approaches, is not restricted to a particular scale and does not require the computation of the thinned pattern. The new proposal, as well as other existing approaches in the bibliography, are evaluated in a common framework for the first time. The performance analysis is based on two manually segmented image data sets: DRIVE retinal image database and COLON-VESSEL data set, a newly created data set of vascular content in colonoscopy frames. We have created an intersection landmark ground truth for each data set besides comparing our method in the only existing ground truth. Quantitative results confirm that we are able to outperform state-of-the-art performancelevels with the advantage that neither training nor parameter tuning is needed. |
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;SIAI |
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Admin @ si @MBS2015 |
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2777 |
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Gloria Fernandez Esparrach; Jorge Bernal; Maria Lopez Ceron; Henry Cordova; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; F. Javier Sanchez |
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Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2016 |
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Endoscopy |
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END |
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48 |
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9 |
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837-842 |
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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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MV; |
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Admin @ si @FBL2016 |
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2778 |
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Francesco Ciompi; Simone Balocco; Juan Rigla; Xavier Carrillo; Josefina Mauri; Petia Radeva |
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Computer-Aided Detection of Intra-Coronary Stent in Intravascular Ultrasound Sequences |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2016 |
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Medical Physics |
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MP |
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43 |
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10 |
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Purpose: An intraluminal coronary stent is a metal mesh tube deployed in a stenotic artery during Percutaneous Coronary Intervention (PCI), in order to prevent acute vessel occlusion. The identication of struts location and the denition of the stent shape are relevant for PCI planning 15 and for patient follow-up. We present a fully-automatic framework for Computer-Aided Detection
(CAD) of intra-coronary stents in Intravascular Ultrasound (IVUS) image sequences. The CAD system is able to detect stent struts and estimate the stent shape.
Methods: The proposed CAD uses machine learning to provide a comprehensive interpretation of the local structure of the vessel by means of semantic classication. The output of the classication 20 stage is then used to detect struts and to estimate the stent shape. The proposed approach is validated using a multi-centric data-set of 1,015 images from 107 IVUS sequences containing both metallic and bio-absorbable stents.
Results: The method was able to detect structs in both metallic stents with an overall F-measure of 77.7% and a mean distance of 0.15 mm from manually annotated struts, and in bio-absorbable 25 stents with an overall F-measure of 77.4% and a mean distance of 0.09 mm from manually annotated struts.
Conclusions: The results are close to the inter-observer variability and suggest that the system has the potential of being used as method for aiding percutaneous interventions. |
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MILAB |
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Admin @ si @ CBR2016 |
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2819 |
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Jean-Pascal Jacob; Mariella Dimiccoli; L. Moisan |
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Active skeleton for bacteria modelling |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2017 |
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Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization |
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CMBBE |
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5 |
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4 |
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274-286 |
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The investigation of spatio-temporal dynamics of bacterial cells and their molecular components requires automated image analysis tools to track cell shape properties and molecular component locations inside the cells. In the study of bacteria aging, the molecular components of interest are protein aggregates accumulated near bacteria boundaries. This particular location makes very ambiguous the correspondence between aggregates and cells, since computing accurately bacteria boundaries in phase-contrast time-lapse imaging is a challenging task. This paper proposes an active skeleton formulation for bacteria modelling which provides several advantages: an easy computation of shape properties (perimeter, length, thickness and orientation), an improved boundary accuracy in noisy images and a natural bacteria-centred coordinate system that permits the intrinsic location of molecular components inside the cell. Starting from an initial skeleton estimate, the medial axis of the bacterium is obtained by minimising an energy function which incorporates bacteria shape constraints. Experimental results on biological images and comparative evaluation of the performances validate the proposed approach for modelling cigar-shaped bacteria like Escherichia coli. The Image-J plugin of the proposed method can be found online at http://fluobactracker.inrialpes.fr. |
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Taylor & Francis Group |
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MILAB; |
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Admin @ si @JDM2017 |
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2784 |
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A.S. Coquel; Jean-Pascal Jacob; M. Primet; A. Demarez; Mariella Dimiccoli; T. Julou; L. Moisan; A. Lindner; H. Berry |
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Localization of protein aggregation in Escherichia coli is governed by diffusion and nucleoid macromolecular crowding effect |
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2013 |
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Plos Computational Biology |
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PCB |
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9 |
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4 |
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Aggregates of misfolded proteins are a hallmark of many age-related diseases. Recently, they have been linked to aging of Escherichia coli (E. coli) where protein aggregates accumulate at the old pole region of the aging bacterium. Because of the potential of E. coli as a model organism, elucidating aging and protein aggregation in this bacterium may pave the way to significant advances in our global understanding of aging. A first obstacle along this path is to decipher the mechanisms by which protein aggregates are targeted to specific intercellular locations. Here, using an integrated approach based on individual-based modeling, time-lapse fluorescence microscopy and automated image analysis, we show that the movement of aging-related protein aggregates in E. coli is purely diffusive (Brownian). Using single-particle tracking of protein aggregates in live E. coli cells, we estimated the average size and diffusion constant of the aggregates. Our results provide evidence that the aggregates passively diffuse within the cell, with diffusion constants that depend on their size in agreement with the Stokes-Einstein law. However, the aggregate displacements along the cell long axis are confined to a region that roughly corresponds to the nucleoid-free space in the cell pole, thus confirming the importance of increased macromolecular crowding in the nucleoids. We thus used 3D individual-based modeling to show that these three ingredients (diffusion, aggregation and diffusion hindrance in the nucleoids) are sufficient and necessary to reproduce the available experimental data on aggregate localization in the cells. Taken together, our results strongly support the hypothesis that the localization of aging-related protein aggregates in the poles of E. coli results from the coupling of passive diffusion-aggregation with spatially non-homogeneous macromolecular crowding. They further support the importance of “soft” intracellular structuring (based on macromolecular crowding) in diffusion-based protein localization in E. coli. |
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: Stanislav Shvartsman, Princeton University, United States of America |
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Admin @ si @CJP2013 |
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2786 |
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Mariella Dimiccoli; Benoît Girard; Alain Berthoz; Daniel Bennequin |
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Striola Magica: a functional explanation of otolith organs |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2013 |
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Journal of Computational Neuroscience |
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JCN |
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35 |
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2 |
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125-154 |
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Otolith organs ;Striola; Vestibular pathway |
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Otolith end organs of vertebrates sense linear accelerations of the head and gravitation. The hair cells on their epithelia are responsible for transduction. In mammals, the striola, parallel to the line where hair cells reverse their polarization, is a narrow region centered on a curve with curvature and torsion. It has been shown that the striolar region is functionally different from the rest, being involved in a phasic vestibular pathway. We propose a mathematical and computational model that explains the necessity of this amazing geometry for the striola to be able to carry out its function. Our hypothesis, related to the biophysics of the hair cells and to the physiology of their afferent neurons, is that striolar afferents collect information from several type I hair cells to detect the jerk in a large domain of acceleration directions. This predicts a mean number of two calyces for afferent neurons, as measured in rodents. The domain of acceleration directions sensed by our striolar model is compatible with the experimental results obtained on monkeys considering all afferents. Therefore, the main result of our study is that phasic and tonic vestibular afferents cover the same geometrical fields, but at different dynamical and frequency domains. |
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Springer US |
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1573-6873. 2013 |
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MILAB |
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Admin @ si @DBG2013 |
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2787 |
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Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias; A. Moreira |
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Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives |
Type ![sorted by Type field, ascending order (up)](img/sort_asc.gif) |
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2016 |
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Robotics and Autonomous Systems |
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RAS |
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83 |
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312-325 |
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Incremental scene reconstruction; Point clouds; Autonomous vehicles; Polygonal primitives |
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When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques. |
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Elsevier B.V. |
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ADAS; 600.086, 600.076 |
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Admin @ si @OSS2016a |
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2806 |
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