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Author | Sumit K. Banchhor; Tadashi Araki; Narendra D. Londhe; Nobutaka Ikeda; Petia Radeva; Ayman El-Baz; Luca Saba; Andrew Nicolaides; Shoaib Shafique; John R. Laird; Jasjit S. Suri | ||||
Title | Five multiresolution-based calcium volume measurement techniques from coronary IVUS videos: A comparative approach | Type | Journal Article | ||
Year | 2016 | Publication | Computer Methods and Programs in Biomedicine | Abbreviated Journal | CMPB |
Volume | 134 | Issue | Pages | 237-258 | |
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Abstract | BACKGROUND AND OBJECTIVE:
Fast intravascular ultrasound (IVUS) video processing is required for calcium volume computation during the planning phase of percutaneous coronary interventional (PCI) procedures. Nonlinear multiresolution techniques are generally applied to improve the processing time by down-sampling the video frames. METHODS: This paper presents four different segmentation methods for calcium volume measurement, namely Threshold-based, Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) embedded with five different kinds of multiresolution techniques (bilinear, bicubic, wavelet, Lanczos, and Gaussian pyramid). This leads to 20 different kinds of combinations. IVUS image data sets consisting of 38,760 IVUS frames taken from 19 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/sec.). The performance of these 20 systems is compared with and without multiresolution using the following metrics: (a) computational time; (b) calcium volume; (c) image quality degradation ratio; and (d) quality assessment ratio. RESULTS: Among the four segmentation methods embedded with five kinds of multiresolution techniques, FCM segmentation combined with wavelet-based multiresolution gave the best performance. FCM and wavelet experienced the highest percentage mean improvement in computational time of 77.15% and 74.07%, respectively. Wavelet interpolation experiences the highest mean precision-of-merit (PoM) of 94.06 ± 3.64% and 81.34 ± 16.29% as compared to other multiresolution techniques for volume level and frame level respectively. Wavelet multiresolution technique also experiences the highest Jaccard Index and Dice Similarity of 0.7 and 0.8, respectively. Multiresolution is a nonlinear operation which introduces bias and thus degrades the image. The proposed system also provides a bias correction approach to enrich the system, giving a better mean calcium volume similarity for all the multiresolution-based segmentation methods. After including the bias correction, bicubic interpolation gives the largest increase in mean calcium volume similarity of 4.13% compared to the rest of the multiresolution techniques. The system is automated and can be adapted in clinical settings. CONCLUSIONS: We demonstrated the time improvement in calcium volume computation without compromising the quality of IVUS image. Among the 20 different combinations of multiresolution with calcium volume segmentation methods, the FCM embedded with wavelet-based multiresolution gave the best performance. |
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Notes | MILAB; | Approved | no | ||
Call Number | Admin @ si @ BAL2016 | Serial | 2830 | ||
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Author | Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva | ||||
Title | Multi-face tracking by extended bag-of-tracklets in egocentric photo-streams | Type | Journal Article | ||
Year | 2016 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
Volume | 149 | Issue | Pages | 146-156 | |
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Abstract | Wearable cameras offer a hands-free way to record egocentric images of daily experiences, where social events are of special interest. The first step towards detection of social events is to track the appearance of multiple persons involved in them. In this paper, we propose a novel method to find correspondences of multiple faces in low temporal resolution egocentric videos acquired through a wearable camera. This kind of photo-stream imposes additional challenges to the multi-tracking problem with respect to conventional videos. Due to the free motion of the camera and to its low temporal resolution, abrupt changes in the field of view, in illumination condition and in the target location are highly frequent. To overcome such difficulties, we propose a multi-face tracking method that generates a set of tracklets through finding correspondences along the whole sequence for each detected face and takes advantage of the tracklets redundancy to deal with unreliable ones. Similar tracklets are grouped into the so called extended bag-of-tracklets (eBoT), which is aimed to correspond to a specific person. Finally, a prototype tracklet is extracted for each eBoT, where the occurred occlusions are estimated by relying on a new measure of confidence. We validated our approach over an extensive dataset of egocentric photo-streams and compared it to state of the art methods, demonstrating its effectiveness and robustness. | ||||
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Notes | MILAB; | Approved | no | ||
Call Number | Admin @ si @ ADR2016b | Serial | 2742 | ||
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Author | Gerard Canal; Sergio Escalera; Cecilio Angulo | ||||
Title | A Real-time Human-Robot Interaction system based on gestures for assistive scenarios | Type | Journal Article | ||
Year | 2016 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
Volume | 149 | Issue | Pages | 65-77 | |
Keywords | Gesture recognition; Human Robot Interaction; Dynamic Time Warping; Pointing location estimation | ||||
Abstract | 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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Publisher | Elsevier B.V. | Place of Publication | Editor | ||
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Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ CEA2016 | Serial | 2768 | ||
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Author | Gloria Fernandez Esparrach; Jorge Bernal; Maria Lopez Ceron; Henry Cordova; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; F. Javier Sanchez | ||||
Title | Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps | Type | Journal Article | ||
Year | 2016 | Publication | Endoscopy | Abbreviated Journal | END |
Volume | 48 | Issue | 9 | Pages | 837-842 |
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Abstract | Background and aims: Polyp miss-rate is a drawback of colonoscopy that increases significantly in small polyps. We explored the efficacy of an automatic computer vision method for polyp detection.
Methods: Our method relies on a model that defines polyp boundaries as valleys of image intensity. Valley information is integrated into energy maps which represent the likelihood of polyp presence. Results: In 24 videos containing polyps from routine colonoscopies, all polyps were detected in at least one frame. Mean values of the maximum of energy map were higher in frames with polyps than without (p<0.001). Performance improved in high quality frames (AUC= 0.79, 95%CI: 0.70-0.87 vs 0.75, 95%CI: 0.66-0.83). Using 3.75 as maximum threshold value, sensitivity and specificity for detection of polyps were 70.4% (95%CI: 60.3-80.8) and 72.4% (95%CI: 61.6-84.6), respectively. Conclusion: Energy maps showed a good performance for colonic polyp detection. This indicates a potential applicability in clinical practice. |
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Notes | MV; | Approved | no | ||
Call Number | Admin @ si @FBL2016 | Serial | 2778 | ||
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Author | Marc Sunset Perez; Marc Comino Trinidad; Dimosthenis Karatzas; Antonio Chica Calaf; Pere Pau Vazquez Alcocer | ||||
Title | Development of general‐purpose projection‐based augmented reality systems | Type | Journal | ||
Year | 2016 | Publication | IADIs international journal on computer science and information systems | Abbreviated Journal | IADIs |
Volume | 11 | Issue | 2 | Pages | 1-18 |
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Abstract | Despite the large amount of methods and applications of augmented reality, there is little homogenizatio n on the software platforms that support them. An exception may be the low level control software that is provided by some high profile vendors such as Qualcomm and Metaio. However, these provide fine grain modules for e.g. element tracking. We are more co ncerned on the application framework, that includes the control of the devices working together for the development of the AR experience. In this paper we describe the development of a software framework for AR setups. We concentrate on the modular design of the framework, but also on some hard problems such as the calibration stage, crucial for projection – based AR. The developed framework is suitable and has been tested in AR applications using camera – projector pairs, for both fixed and nomadic setups | ||||
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Notes | DAG; 600.084 | Approved | no | ||
Call Number | Admin @ si @ SCK2016 | Serial | 2890 | ||
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Author | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
Title | Hierarchical Adaptive Structural SVM for Domain Adaptation | Type | Journal Article | ||
Year | 2016 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
Volume | 119 | Issue | 2 | Pages | 159-178 |
Keywords | Domain Adaptation; Pedestrian Detection | ||||
Abstract | A key topic in classification is the accuracy loss produced when the data distribution in the training (source) domain differs from that in the testing (target) domain. This is being recognized as a very relevant problem for many
computer vision tasks such as image classification, object detection, and object category recognition. In this paper, we present a novel domain adaptation method that leverages multiple target domains (or sub-domains) in a hierarchical adaptation tree. The core idea is to exploit the commonalities and differences of the jointly considered target domains. Given the relevance of structural SVM (SSVM) classifiers, we apply our idea to the adaptive SSVM (A-SSVM), which only requires the target domain samples together with the existing source-domain classifier for performing the desired adaptation. Altogether, we term our proposal as hierarchical A-SSVM (HA-SSVM). As proof of concept we use HA-SSVM for pedestrian detection, object category recognition and face recognition. In the former we apply HA-SSVM to the deformable partbased model (DPM) while in the rest HA-SSVM is applied to multi-category classifiers. We will show how HA-SSVM is effective in increasing the detection/recognition accuracy with respect to adaptation strategies that ignore the structure of the target data. Since, the sub-domains of the target data are not always known a priori, we shown how HA-SSVM can incorporate sub-domain discovery for object category recognition. |
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Publisher | Springer US | Place of Publication | Editor | ||
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ISSN | 0920-5691 | ISBN | Medium | ||
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Notes | ADAS; 600.085; 600.082; 600.076 | Approved | no | ||
Call Number | Admin @ si @ XRV2016 | Serial | 2669 | ||
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Author | Antonio Hernandez; Sergio Escalera; Stan Sclaroff | ||||
Title | Poselet-basedContextual Rescoring for Human Pose Estimation via Pictorial Structures | Type | Journal Article | ||
Year | 2016 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
Volume | 118 | Issue | 1 | Pages | 49–64 |
Keywords | Contextual rescoring; Poselets; Human pose estimation | ||||
Abstract | In this paper we propose a contextual rescoring method for predicting the position of body parts in a human pose estimation framework. A set of poselets is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body part hypotheses. A method is proposed for the automatic discovery of a compact subset of poselets that covers the different poses in a set of validation images while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for each body joint detection, given its relationship to detections of other body joints and mid-level parts in the image. This new score is incorporated in the pictorial structure model as an additional unary potential, following the recent work of Pishchulin et al. Experiments on two benchmarks show comparable results to Pishchulin et al. while reducing the size of the mid-level representation by an order of magnitude, reducing the execution time by 68 % accordingly. | ||||
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Publisher | Springer US | Place of Publication | Editor | ||
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ISSN | 0920-5691 | ISBN | Medium | ||
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Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ HES2016 | Serial | 2719 | ||
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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 | Lluis Gomez; Dimosthenis Karatzas | ||||
Title | A fast hierarchical method for multi‐script and arbitrary oriented scene text extraction | Type | Journal Article | ||
Year | 2016 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
Volume | 19 | Issue | 4 | Pages | 335-349 |
Keywords | scene text; segmentation; detection; hierarchical grouping; perceptual organisation | ||||
Abstract | Typography and layout lead to the hierarchical organisation of text in words, text lines, paragraphs. This inherent structure is a key property of text in any script and language, which has nonetheless been minimally leveraged by existing text detection methods. This paper addresses the problem of text
segmentation in natural scenes from a hierarchical perspective. Contrary to existing methods, we make explicit use of text structure, aiming directly to the detection of region groupings corresponding to text within a hierarchy produced by an agglomerative similarity clustering process over individual regions. We propose an optimal way to construct such an hierarchy introducing a feature space designed to produce text group hypotheses with high recall and a novel stopping rule combining a discriminative classifier and a probabilistic measure of group meaningfulness based in perceptual organization. Results obtained over four standard datasets, covering text in variable orientations and different languages, demonstrate that our algorithm, while being trained in a single mixed dataset, outperforms state of the art methods in unconstrained scenarios. |
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Notes | DAG; 600.056; 601.197 | Approved | no | ||
Call Number | Admin @ si @ GoK2016a | Serial | 2862 | ||
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Author | Maria Oliver; G. Haro; Mariella Dimiccoli; B. Mazin; C. Ballester | ||||
Title | A Computational Model for Amodal Completion | Type | Journal Article | ||
Year | 2016 | Publication | Journal of Mathematical Imaging and Vision | Abbreviated Journal | JMIV |
Volume | 56 | Issue | 3 | Pages | 511–534 |
Keywords | Perception; visual completion; disocclusion; Bayesian model;relatability; Euler elastica | ||||
Abstract | This paper presents a computational model to recover the most likely interpretation
of the 3D scene structure from a planar image, where some objects may occlude others. The estimated scene interpretation is obtained by integrating some global and local cues and provides both the complete disoccluded objects that form the scene and their ordering according to depth. Our method first computes several distal scenes which are compatible with the proximal planar image. To compute these different hypothesized scenes, we propose a perceptually inspired object disocclusion method, which works by minimizing the Euler's elastica as well as by incorporating the relatability of partially occluded contours and the convexity of the disoccluded objects. Then, to estimate the preferred scene we rely on a Bayesian model and define probabilities taking into account the global complexity of the objects in the hypothesized scenes as well as the effort of bringing these objects in their relative position in the planar image, which is also measured by an Euler's elastica-based quantity. The model is illustrated with numerical experiments on, both, synthetic and real images showing the ability of our model to reconstruct the occluded objects and the preferred perceptual order among them. We also present results on images of the Berkeley dataset with provided figure-ground ground-truth labeling. |
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Notes | MILAB; 601.235 | Approved | no | ||
Call Number | Admin @ si @ OHD2016b | Serial | 2745 | ||
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Author | Sergio Escalera; Vassilis Athitsos; Isabelle Guyon | ||||
Title | Challenges in multimodal gesture recognition | Type | Journal Article | ||
Year | 2016 | Publication | Journal of Machine Learning Research | Abbreviated Journal | JMLR |
Volume | 17 | Issue | Pages | 1-54 | |
Keywords | Gesture Recognition; Time Series Analysis; Multimodal Data Analysis; Computer Vision; Pattern Recognition; Wearable sensors; Infrared Cameras; KinectTM | ||||
Abstract | 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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Publisher | Place of Publication | Editor | Zhuowen Tu | ||
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Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ EAG2016 | Serial | 2764 | ||
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Author | Tadashi Araki; Sumit K. Banchhor; Narendra D. Londhe; Nobutaka Ikeda; Petia Radeva; Devarshi Shukla; Luca Saba; Antonella Balestrieri; Andrew Nicolaides; Shoaib Shafique; John R. Laird; Jasjit S. Suri | ||||
Title | Reliable and Accurate Calcium Volume Measurement in Coronary Artery Using Intravascular Ultrasound Videos | Type | Journal Article | ||
Year | 2016 | Publication | Journal of Medical Systems | Abbreviated Journal | JMS |
Volume | 40 | Issue | 3 | Pages | 51:1-51:20 |
Keywords | Interventional cardiology; Atherosclerosis; Coronary arteries; IVUS; calcium volume; Soft computing; Performance Reliability; Accuracy | ||||
Abstract | Quantitative assessment of calcified atherosclerotic volume within the coronary artery wall is vital for cardiac interventional procedures. The goal of this study is to automatically measure the calcium volume, given the borders of coronary vessel wall for all the frames of the intravascular ultrasound (IVUS) video. Three soft computing fuzzy classification techniques were adapted namely Fuzzy c-Means (FCM), K-means, and Hidden Markov Random Field (HMRF) for automated segmentation of calcium regions and volume computation. These methods were benchmarked against previously developed threshold-based method. IVUS image data sets (around 30,600 IVUS frames) from 15 patients were collected using 40 MHz IVUS catheter (Atlantis® SR Pro, Boston Scientific®, pullback speed of 0.5 mm/s). Calcium mean volume for FCM, K-means, HMRF and threshold-based method were 37.84 ± 17.38 mm3, 27.79 ± 10.94 mm3, 46.44 ± 19.13 mm3 and 35.92 ± 16.44 mm3 respectively. Cross-correlation, Jaccard Index and Dice Similarity were highest between FCM and threshold-based method: 0.99, 0.92 ± 0.02 and 0.95 + 0.02 respectively. Student’s t-test, z-test and Wilcoxon-test are also performed to demonstrate consistency, reliability and accuracy of the results. Given the vessel wall region, the system reliably and automatically measures the calcium volume in IVUS videos. Further, we validated our system against a trained expert using scoring: K-means showed the best performance with an accuracy of 92.80 %. Out procedure and protocol is along the line with method previously published clinically. | ||||
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Notes | MILAB; | Approved | no | ||
Call Number | Admin @ si @ ABL2016 | Serial | 2729 | ||
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Author | Pejman Rasti; Salma Samiei; Mary Agoyi; Sergio Escalera; Gholamreza Anbarjafari | ||||
Title | Robust non-blind color video watermarking using QR decomposition and entropy analysis | Type | Journal Article | ||
Year | 2016 | Publication | Journal of Visual Communication and Image Representation | Abbreviated Journal | JVCIR |
Volume | 38 | Issue | Pages | 838-847 | |
Keywords | Video watermarking; QR decomposition; Discrete Wavelet Transformation; Chirp Z-transform; Singular value decomposition; Orthogonal–triangular decomposition | ||||
Abstract | 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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Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @RSA2016 | Serial | 2766 | ||
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Author | Francesco Ciompi; Simone Balocco; Juan Rigla; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
Title | Computer-Aided Detection of Intra-Coronary Stent in Intravascular Ultrasound Sequences | Type | Journal Article | ||
Year | 2016 | Publication | Medical Physics | Abbreviated Journal | MP |
Volume | 43 | Issue | 10 | Pages | |
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Abstract | 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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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ CBR2016 | Serial | 2819 | ||
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Author | Svebor Karaman; Andrew Bagdanov; Lea Landucci; Gianpaolo D'Amico; Andrea Ferracani; Daniele Pezzatini; Alberto del Bimbo | ||||
Title | Personalized multimedia content delivery on an interactive table by passive observation of museum visitors | Type | Journal Article | ||
Year | 2016 | Publication | Multimedia Tools and Applications | Abbreviated Journal | MTAP |
Volume | 75 | Issue | 7 | Pages | 3787-3811 |
Keywords | Computer vision; Video surveillance; Cultural heritage; Multimedia museum; Personalization; Natural interaction; Passive profiling | ||||
Abstract | The amount of multimedia data collected in museum databases is growing fast, while the capacity of museums to display information to visitors is acutely limited by physical space. Museums must seek the perfect balance of information given on individual pieces in order to provide sufficient information to aid visitor understanding while maintaining sparse usage of the walls and guaranteeing high appreciation of the exhibit. Moreover, museums often target the interests of average visitors instead of the entire spectrum of different interests each individual visitor might have. Finally, visiting a museum should not be an experience contained in the physical space of the museum but a door opened onto a broader context of related artworks, authors, artistic trends, etc. In this paper we describe the MNEMOSYNE system that attempts to address these issues through a new multimedia museum experience. Based on passive observation, the system builds a profile of the artworks of interest for each visitor. These profiles of interest are then used to drive an interactive table that personalizes multimedia content delivery. The natural user interface on the interactive table uses the visitor’s profile, an ontology of museum content and a recommendation system to personalize exploration of multimedia content. At the end of their visit, the visitor can take home a personalized summary of their visit on a custom mobile application. In this article we describe in detail each component of our approach as well as the first field trials of our prototype system built and deployed at our permanent exhibition space at LeMurate (http://www.lemurate.comune.fi.it/lemurate/) in Florence together with the first results of the evaluation process during the official installation in the National Museum of Bargello (http://www.uffizi.firenze.it/musei/?m=bargello). | ||||
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Publisher | Springer US | Place of Publication | Editor | ||
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ISSN | 1380-7501 | ISBN | Medium | ||
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Notes | LAMP; 601.240; 600.079 | Approved | no | ||
Call Number | Admin @ si @ KBL2016 | Serial | 2520 | ||
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