The problem of generic object recognition is discussed in relation to the current research emphasis in the computer vision community on learning methods for classz~cationM. utual information is proposed as a tool for identiying the salient features of a class and as a mechanism for constructing class recognizers from an engineering design standpoint. The concept of obsewability is introduced to define classes that may differ from human concepts but are necessary to achieve high recognition performance.
{"title":"Generic Object Recognizer Design","authors":"J. Mundy","doi":"10.1109/CVIIE.2005.9","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.9","url":null,"abstract":"The problem of generic object recognition is discussed in relation to the current research emphasis in the computer vision community on learning methods for classz~cationM. utual information is proposed as a tool for identiying the salient features of a class and as a mechanism for constructing class recognizers from an engineering design standpoint. The concept of obsewability is introduced to define classes that may differ from human concepts but are necessary to achieve high recognition performance.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129839291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traditional desktop computing paradigms provide a poor interface for interacting with intelligent physical spaces. Although handheld devices are an important platform for interface agents, their displays are inadequate for many pervasive computing tasks and need to be supplemented by larger high-resolution displays. We propose the notion of augmenting indoor intelligent environments with ambient projection, where large numbers of projectors simultaneously illuminate the environment from multiple directions - analogous to the way in which ambient lighting permeates a room. Ambient projection could enable any suitable surface in an environment to be employed as a display device. Using such displays, the intelligent environment could present high-resolution information, proactively alert users who are not carrying handheld devices and annotate objects in the environment without instrumentation. Several challenges must be solved before such projected displays become a practical solution. This paper provides an overview of our research in computer vision for enabling interactive ambient projected displays.
{"title":"Towards Ambient Projection for Intelligent Environments","authors":"Rahul Sukthankar","doi":"10.1109/CVIIE.2005.20","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.20","url":null,"abstract":"Traditional desktop computing paradigms provide a poor interface for interacting with intelligent physical spaces. Although handheld devices are an important platform for interface agents, their displays are inadequate for many pervasive computing tasks and need to be supplemented by larger high-resolution displays. We propose the notion of augmenting indoor intelligent environments with ambient projection, where large numbers of projectors simultaneously illuminate the environment from multiple directions - analogous to the way in which ambient lighting permeates a room. Ambient projection could enable any suitable surface in an environment to be employed as a display device. Using such displays, the intelligent environment could present high-resolution information, proactively alert users who are not carrying handheld devices and annotate objects in the environment without instrumentation. Several challenges must be solved before such projected displays become a practical solution. This paper provides an overview of our research in computer vision for enabling interactive ambient projected displays.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"451 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123022394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A first step towards an understanding of the semantic content in a video is the reliable detection and recognition of actions performed by objects in the environment. This is a difficult problem due to the enormous variability in an action's appearance when seen from different viewpoints and/or at different times. In this paper we present a novel approach to representing actions that models actions as specific types of 3d objects. Specifically, we observe that any action can be represented as a generalized cylinder, called the action cylinder. Visualizing actions as objects allows rigid, articulated, and non-rigid actions to all be modeled in a uniform framework.
{"title":"Representing Actions of Objects in Intelligent Environments","authors":"T. Syeda-Mahmood","doi":"10.1109/CVIIE.2005.17","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.17","url":null,"abstract":"A first step towards an understanding of the semantic content in a video is the reliable detection and recognition of actions performed by objects in the environment. This is a difficult problem due to the enormous variability in an action's appearance when seen from different viewpoints and/or at different times. In this paper we present a novel approach to representing actions that models actions as specific types of 3d objects. Specifically, we observe that any action can be represented as a generalized cylinder, called the action cylinder. Visualizing actions as objects allows rigid, articulated, and non-rigid actions to all be modeled in a uniform framework.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125583369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Interactive, Intelligent Environments involve a convergence of various research themes, including high-fidelity visualization, communication, gestural expression, and virtualized reality systems. Recent advances in real-time acquisition, transmission, and rendering of multimodal data (e.g. audio, video, haptic) allow for the synthesis of significantly improved perceptual representations of a virtual or real (e.g. remote) environment than were previously possible. Furthermore, increased computational power permits the synthesis of a rich responsive media space that responds to a large number of participants engaged in a complex, expressive activity. Unfortunately, current systems tend to concentrate almost exclusively on one aspect or the other, supporting the representation and interaction with a virtual world, or supporting distributed human communication, but never both. The ideal interactive intelligent environment is one that permits effective distributed human-human communication among large numbers of participants at multiple locations, simultaneously with data visualization capabilities and interaction with dynamic, synthetic objects. A significant challenge for the next generation of such environments is to develop the necessary physical infrastructures and software architectures that combine these capabilities appropriately.
{"title":"Integrating Communication with Interaction: Computer Vision Challenges for Interactive and Intelligent Environments","authors":"J. Cooperstock","doi":"10.1109/CVIIE.2005.10","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.10","url":null,"abstract":"Interactive, Intelligent Environments involve a convergence of various research themes, including high-fidelity visualization, communication, gestural expression, and virtualized reality systems. Recent advances in real-time acquisition, transmission, and rendering of multimodal data (e.g. audio, video, haptic) allow for the synthesis of significantly improved perceptual representations of a virtual or real (e.g. remote) environment than were previously possible. Furthermore, increased computational power permits the synthesis of a rich responsive media space that responds to a large number of participants engaged in a complex, expressive activity. Unfortunately, current systems tend to concentrate almost exclusively on one aspect or the other, supporting the representation and interaction with a virtual world, or supporting distributed human communication, but never both. The ideal interactive intelligent environment is one that permits effective distributed human-human communication among large numbers of participants at multiple locations, simultaneously with data visualization capabilities and interaction with dynamic, synthetic objects. A significant challenge for the next generation of such environments is to develop the necessary physical infrastructures and software architectures that combine these capabilities appropriately.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116428370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Horster, R. Lienhart, Walter Kellermann, J. Bouguet
Many novel multimedia, home entertainment, visual surveillance and health applications use multiple audio-visual sensors and actuators. In this paper we present a novel approach for position and pose calibration of visual sensors and actuators, i.e. cameras and displays, in a distributed network of general purpose computing devices. It complements our work on position calibration of audio sensors and actuators in a distributed computing platform [14]. The approach is suitable for a wide range of possible - even mobile - setups since (a) synchronization is not required, (b) it works automatically, (c) only weak restrictions are imposed on the positions of the cameras and displays, and (d) no upper limit on the number of cameras and displays under calibration is imposed. Corresponding points across different camera images are established automatically and found with subpixel accuracy. Cameras do not have to share one common view. Only a reasonable overlap between camera subgroups is necessary. The method has been sucessfully tested in numerous multi-camera environments with a varying number of cameras and displays and has proven itself to work extremely accurate.
{"title":"Calibrating Visual Sensors and Actuators in Distributed Platforms","authors":"E. Horster, R. Lienhart, Walter Kellermann, J. Bouguet","doi":"10.1109/CVIIE.2005.2","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.2","url":null,"abstract":"Many novel multimedia, home entertainment, visual surveillance and health applications use multiple audio-visual sensors and actuators. In this paper we present a novel approach for position and pose calibration of visual sensors and actuators, i.e. cameras and displays, in a distributed network of general purpose computing devices. It complements our work on position calibration of audio sensors and actuators in a distributed computing platform [14]. The approach is suitable for a wide range of possible - even mobile - setups since (a) synchronization is not required, (b) it works automatically, (c) only weak restrictions are imposed on the positions of the cameras and displays, and (d) no upper limit on the number of cameras and displays under calibration is imposed. Corresponding points across different camera images are established automatically and found with subpixel accuracy. Cameras do not have to share one common view. Only a reasonable overlap between camera subgroups is necessary. The method has been sucessfully tested in numerous multi-camera environments with a varying number of cameras and displays and has proven itself to work extremely accurate.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124068941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many human activities follow a loosely defined script in which individuals assume roles. Encoding such scripts in a formal representation makes it possible to build systems that observe and understand human activity. In this paper, we first present a conceptual framework in which scripts for human activity are described as scenarios composed of actors and objects within a network of situations. We provide formal definitions for the underlying concepts for situation models, and then propose a layered, component-based, software architecture model for constructings systems to observe human activity. Both the conceptual framework and architectural model are illustrated with a system for real-time composition of a synchronized audio-video streams for recording activity within a meeting or lecture.
{"title":"Situated Observation of Human Activity","authors":"J. Crowley","doi":"10.1109/CVIIE.2005.18","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.18","url":null,"abstract":"Many human activities follow a loosely defined script in which individuals assume roles. Encoding such scripts in a formal representation makes it possible to build systems that observe and understand human activity. In this paper, we first present a conceptual framework in which scripts for human activity are described as scenarios composed of actors and objects within a network of situations. We provide formal definitions for the underlying concepts for situation models, and then propose a layered, component-based, software architecture model for constructings systems to observe human activity. Both the conceptual framework and architectural model are illustrated with a system for real-time composition of a synchronized audio-video streams for recording activity within a meeting or lecture.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128869078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Motion capture has important applications in different areas such as biomechanics, computer animation, and human-computer interaction. Current motion capture methods use passive markers that are attached to different body parts of the subject and are therefore intrusive in nature. In applications such as pathological human movement analysis, these markers may introduce an unknown artifact in the motion, and are, in general, cumbersome. We present computer vision based methods for performing markerless human motion capture. We model the human body as a set of super-quadrics connected in an articulated structure and propose algorithms to estimate the parameters of the model from video sequences. We compute a volume data (voxel) representation from the images and combine bottom-up approach with top down approach guided by our knowledge of the model. We propose a tracking algorithm that uses this model to track human pose. The tracker uses an iterative framework akin to an Iterated Extended Kalman Filter to estimate articulated human motion using multiple cues that combine both spatial and temporal information in a novel manner. We provide preliminary results using data collected from 8-16 cameras. The emphasis of our work is on models and algorithms that are able to scale with respect to the requirement for accuracy. Our ultimate objective is to build an end-to-end system that can integrate the above mentioned components into a completely automated markerless motion capture system.
{"title":"Markerless Motion Capture using Multiple Cameras","authors":"A. Sundaresan, R. Chellappa","doi":"10.1109/CVIIE.2005.13","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.13","url":null,"abstract":"Motion capture has important applications in different areas such as biomechanics, computer animation, and human-computer interaction. Current motion capture methods use passive markers that are attached to different body parts of the subject and are therefore intrusive in nature. In applications such as pathological human movement analysis, these markers may introduce an unknown artifact in the motion, and are, in general, cumbersome. We present computer vision based methods for performing markerless human motion capture. We model the human body as a set of super-quadrics connected in an articulated structure and propose algorithms to estimate the parameters of the model from video sequences. We compute a volume data (voxel) representation from the images and combine bottom-up approach with top down approach guided by our knowledge of the model. We propose a tracking algorithm that uses this model to track human pose. The tracker uses an iterative framework akin to an Iterated Extended Kalman Filter to estimate articulated human motion using multiple cues that combine both spatial and temporal information in a novel manner. We provide preliminary results using data collected from 8-16 cameras. The emphasis of our work is on models and algorithms that are able to scale with respect to the requirement for accuracy. Our ultimate objective is to build an end-to-end system that can integrate the above mentioned components into a completely automated markerless motion capture system.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128116616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a model-based 3D object tracking system that uses an improved Extended Kalman filter (EKF) with graphics rendering as the measurement function. During tracking, features are automatically selected from the input images. For each camera, an estimated observation and multiple perturbed observations are rendered for the object. Corresponding features are extracted from the sample images, and their estimated/perturbed measurements are acquired. These sample measurements and the real measurements of the features are then sent to an extended EKF (EEKF). Finally, the EEKF uses the sample measurements to compute high order approximations of the nonlinear measurement functions, and updates the state estimate of the object in an iterative form. The system is scalable to different types of renderable models and measureable features. We present results showing that the approach can be used to track a rigid object, from multiple views, in real-time.
{"title":"Model-Based 3D Object Tracking Using an Extended-Extended Kalman Filter and Graphics Rendered Measurements","authors":"Hua Yang, G. Welch","doi":"10.1109/CVIIE.2005.14","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.14","url":null,"abstract":"This paper presents a model-based 3D object tracking system that uses an improved Extended Kalman filter (EKF) with graphics rendering as the measurement function. During tracking, features are automatically selected from the input images. For each camera, an estimated observation and multiple perturbed observations are rendered for the object. Corresponding features are extracted from the sample images, and their estimated/perturbed measurements are acquired. These sample measurements and the real measurements of the features are then sent to an extended EKF (EEKF). Finally, the EEKF uses the sample measurements to compute high order approximations of the nonlinear measurement functions, and updates the state estimate of the object in an iterative form. The system is scalable to different types of renderable models and measureable features. We present results showing that the approach can be used to track a rigid object, from multiple views, in real-time.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123858384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
One of the persistent challenges in computer vision has been tracking objects under varying lighting conditions. In this paper we present a method for estimation of 3D motion of a rigid object from a monocular video sequence under arbitrary changes in the illumination conditions under which the video was captured. This is achieved by alternately estimating motion and illumination parameters using a generative model for integrating the effects of motion, illumination and structure within a unified mathematical framework. The motion is represented in terms of translation and rotation of the object centroid, and the illumination is represented using a spherical harmonics linear basis. The method does not assume any model for the variation of the illumination conditions - lighting can change slowly or drastically. For the multi-camera tracking scenario, we propose a new photometric constraint that is valid over the overlapping field of view between two cameras. This is similar in nature to the well-known epipolar constraint, except that it relates the photometric parameters, and can provide an additional constraint for illumination invariant multi-camera tracking. We demonstrate the effectiveness of our tracking algorithm on single and multi-camera video sequences under severe changes of lighting conditions.
{"title":"Integrating Motion and Illumination Models for 3D Tracking","authors":"A. Roy-Chowdhury, Yilei Xu","doi":"10.1109/CVIIE.2005.11","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.11","url":null,"abstract":"One of the persistent challenges in computer vision has been tracking objects under varying lighting conditions. In this paper we present a method for estimation of 3D motion of a rigid object from a monocular video sequence under arbitrary changes in the illumination conditions under which the video was captured. This is achieved by alternately estimating motion and illumination parameters using a generative model for integrating the effects of motion, illumination and structure within a unified mathematical framework. The motion is represented in terms of translation and rotation of the object centroid, and the illumination is represented using a spherical harmonics linear basis. The method does not assume any model for the variation of the illumination conditions - lighting can change slowly or drastically. For the multi-camera tracking scenario, we propose a new photometric constraint that is valid over the overlapping field of view between two cameras. This is similar in nature to the well-known epipolar constraint, except that it relates the photometric parameters, and can provide an additional constraint for illumination invariant multi-camera tracking. We demonstrate the effectiveness of our tracking algorithm on single and multi-camera video sequences under severe changes of lighting conditions.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129386620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Signifiicant research progress has been made in intelligent imaging systems, surveillance and biometrics improving robustness, increasing performance and decreasing cost. As a result, deployment of surveillance and intelligent video systems is booming and increasing the impact of these on privacy. For many, networked intelligent video systems, especially video surveillance and biometrics, epitomize the invasion of privacy by an Orwellian "big brother:. While tens of millions in government funding have been spent on research improving video surveillance, virtually none has been invested in technologies to enhance privacy or effectively balance privacy and security. This paper presents an example that demonstrates how using and adapting cryptographic ideas and combining them with intelligent video processing, technological pproaches can provide for solutions addressing these critical trade-offs, potentially improving both security and privacy. After reviewing previous research in privacy improving technology in video systems, the paper then presents cryptographically invertible obscuration. This is an application of encryption techniques to improve the privacy aspects while allowing general surveillance to continue and allowing full access (i.e. violation ofprivacy) only with use of a decryption key, maintained by a court or other thirdparty.
{"title":"PICO: Privacy through Invertible Cryptographic Obscuration","authors":"T. Boult","doi":"10.1109/CVIIE.2005.16","DOIUrl":"https://doi.org/10.1109/CVIIE.2005.16","url":null,"abstract":"Signifiicant research progress has been made in intelligent imaging systems, surveillance and biometrics improving robustness, increasing performance and decreasing cost. As a result, deployment of surveillance and intelligent video systems is booming and increasing the impact of these on privacy. For many, networked intelligent video systems, especially video surveillance and biometrics, epitomize the invasion of privacy by an Orwellian \"big brother:. While tens of millions in government funding have been spent on research improving video surveillance, virtually none has been invested in technologies to enhance privacy or effectively balance privacy and security. This paper presents an example that demonstrates how using and adapting cryptographic ideas and combining them with intelligent video processing, technological pproaches can provide for solutions addressing these critical trade-offs, potentially improving both security and privacy. After reviewing previous research in privacy improving technology in video systems, the paper then presents cryptographically invertible obscuration. This is an application of encryption techniques to improve the privacy aspects while allowing general surveillance to continue and allowing full access (i.e. violation ofprivacy) only with use of a decryption key, maintained by a court or other thirdparty.","PeriodicalId":447061,"journal":{"name":"Computer Vision for Interactive and Intelligent Environment (CVIIE'05)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122980769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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