In this paper, we propose a method for automatic quality of experience (QoE) prediction in stereoscopic videos. QoE, though embodying the subjective measures of the end user's perceived quality, can be expressed in relation to some quality of service (QoS) parameters. Having information on content types in modelling QoE-QoS interactions is advantageous as videos with the same QoS parameters may have different subjective scores due to different content types. Consequently, using content clustering with the help of spatio-temporal activities within depth layers, QoE predictor is designed per each content cluster utilising full reference (FR) and no reference (NR) metrics. Finally, the performance of the proposed QoE prediction algorithm is evaluated extensively and the overall measure of success value equal to 95.4% is achieved for the test sequences. This model can be applied for QoE control in video provisioning systems.
{"title":"Automatic QOE Prediction in Stereoscopic Videos","authors":"H. Malekmohamadi, W. Fernando, A. Kondoz","doi":"10.1109/ICMEW.2012.107","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.107","url":null,"abstract":"In this paper, we propose a method for automatic quality of experience (QoE) prediction in stereoscopic videos. QoE, though embodying the subjective measures of the end user's perceived quality, can be expressed in relation to some quality of service (QoS) parameters. Having information on content types in modelling QoE-QoS interactions is advantageous as videos with the same QoS parameters may have different subjective scores due to different content types. Consequently, using content clustering with the help of spatio-temporal activities within depth layers, QoE predictor is designed per each content cluster utilising full reference (FR) and no reference (NR) metrics. Finally, the performance of the proposed QoE prediction algorithm is evaluated extensively and the overall measure of success value equal to 95.4% is achieved for the test sequences. This model can be applied for QoE control in video provisioning systems.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125424298","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 meme media object, also known as a Webble, always come with a set of familiar generic behaviors together with another set of specialized ones for that particular Webble. But what if there is a need for a custom behavior or interface that was not originally intended when first created. With Webble technology, that does not need to be a problem. In this paper we will attempt to show how simple it is, due to the design and construction of Webbles, to insert new customizable behaviors in any Webble available, or control application level events and actions, all through an intuitive, user-friendly interface. We claim that within a few hours of combining generic Webble building blocks and the setting up of configurable event handlers directly in the web browser, without traditional programming, we can create any arbitrary Silver light-based web application, ready to be shared to the cloud and the world.
{"title":"Advanced \"Webble\" Application Development Directly in the Browser by Utilizing the Full Power of Meme Media Customization and Event Management Capabilities","authors":"M. Kuwahara, Yuzuru Tanaka","doi":"10.1109/ICMEW.2012.43","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.43","url":null,"abstract":"A meme media object, also known as a Webble, always come with a set of familiar generic behaviors together with another set of specialized ones for that particular Webble. But what if there is a need for a custom behavior or interface that was not originally intended when first created. With Webble technology, that does not need to be a problem. In this paper we will attempt to show how simple it is, due to the design and construction of Webbles, to insert new customizable behaviors in any Webble available, or control application level events and actions, all through an intuitive, user-friendly interface. We claim that within a few hours of combining generic Webble building blocks and the setting up of configurable event handlers directly in the web browser, without traditional programming, we can create any arbitrary Silver light-based web application, ready to be shared to the cloud and the world.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124312911","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}
Segmentation of 3D model models has applications, e.g., in mesh editing and 3D model retrieval. Unsupervised, automatic segmentation of 3D models can be useful. However, some applications require user-guided, interactive segmentation that captures user intention. This paper presents a supervised, local-geometry aware segmentation algorithm for 3D mesh models. The algorithm segments manifold meshes based on interactive guidance from users. The method casts user-guided mesh segmentation as a semi-supervised learning problem that propagates segmentation labels given to a subset of faces to the unlabeled faces of a 3D model. The proposed algorithm employs Zhou's Manifold Ranking [18] algorithm, which takes both local and global consistency in high-dimensional feature space for the label propagation. Evaluation using a 3D model segmentation benchmark dataset has shown that the method is effective, although achieving interactivity for a large and complex mesh requires some work.
{"title":"Supervised, Geometry-Aware Segmentation of 3D Mesh Models","authors":"Keisuke Bamba, Ryutarou Ohbuchi","doi":"10.1109/ICMEW.2012.16","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.16","url":null,"abstract":"Segmentation of 3D model models has applications, e.g., in mesh editing and 3D model retrieval. Unsupervised, automatic segmentation of 3D models can be useful. However, some applications require user-guided, interactive segmentation that captures user intention. This paper presents a supervised, local-geometry aware segmentation algorithm for 3D mesh models. The algorithm segments manifold meshes based on interactive guidance from users. The method casts user-guided mesh segmentation as a semi-supervised learning problem that propagates segmentation labels given to a subset of faces to the unlabeled faces of a 3D model. The proposed algorithm employs Zhou's Manifold Ranking [18] algorithm, which takes both local and global consistency in high-dimensional feature space for the label propagation. Evaluation using a 3D model segmentation benchmark dataset has shown that the method is effective, although achieving interactivity for a large and complex mesh requires some work.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130600214","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}
Automatic assessment of image quality in accordance with the human visual system (HVS) finds application in various image processing tasks. In the last decade, a substantial proliferation in image quality assessment (IQA) based on structural similarity has been observed. The structural information estimation includes statistical values (mean, variance, and correlation), gradient information, Harris response and singular values. In this paper, we propose a multiscale image quality metric which exploits the properties of Singular Value Decomposition (SVD) to get approximate pyramid structure for its use in IQA. The proposed multiscale metric has been extensively evaluated in the LIVE database and CSIQ database. Experiments have been carried out on the effective number of scales used as well as on the effective proportion of different scales required for the metric. The proposed metric achieves competitive performance with the structural similarity based state-of-the-art methods.
{"title":"SVD Filter Based Multiscale Approach for Image Quality Assessment","authors":"Ashirbani Saha, G. Bhatnagar, Q.M. Jonathan Wu","doi":"10.1109/ICMEW.2012.15","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.15","url":null,"abstract":"Automatic assessment of image quality in accordance with the human visual system (HVS) finds application in various image processing tasks. In the last decade, a substantial proliferation in image quality assessment (IQA) based on structural similarity has been observed. The structural information estimation includes statistical values (mean, variance, and correlation), gradient information, Harris response and singular values. In this paper, we propose a multiscale image quality metric which exploits the properties of Singular Value Decomposition (SVD) to get approximate pyramid structure for its use in IQA. The proposed multiscale metric has been extensively evaluated in the LIVE database and CSIQ database. Experiments have been carried out on the effective number of scales used as well as on the effective proportion of different scales required for the metric. The proposed metric achieves competitive performance with the structural similarity based state-of-the-art methods.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124627412","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}
Social attributes for photos, which simply refer to a set of labels {Who, When, Where, What}, are intrinsic attributes of an image. For instance, given a scenery photo without human bodies or faces, we cannot say the photo has no relation with social individuals. In fact, it could have been taken when we went travelling with other friends. To effectively annotate social attributes, we obtain training images from friends' SNS albums. Moreover, to cope with limited training data and organize photos in a feature-effective way, we introduce a batch-based framework, which pre-clusters photos by events. After graph learning based annotation, a post processing step is proposed to refine the annotation result. Experimental results show the effectiveness of the proposed batch-based social attribute annotation framework.
{"title":"Social Attribute Annotation for Personal Photo Collection","authors":"Zhipeng Wu, K. Aizawa","doi":"10.1109/ICMEW.2012.47","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.47","url":null,"abstract":"Social attributes for photos, which simply refer to a set of labels {Who, When, Where, What}, are intrinsic attributes of an image. For instance, given a scenery photo without human bodies or faces, we cannot say the photo has no relation with social individuals. In fact, it could have been taken when we went travelling with other friends. To effectively annotate social attributes, we obtain training images from friends' SNS albums. Moreover, to cope with limited training data and organize photos in a feature-effective way, we introduce a batch-based framework, which pre-clusters photos by events. After graph learning based annotation, a post processing step is proposed to refine the annotation result. Experimental results show the effectiveness of the proposed batch-based social attribute annotation framework.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122335646","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}
Rene Kaiser, Wolfgang Weiss, Manolis Falelakis, Spiros Michalakopoulos, M. Ursu
Audiovisual group communication systems deal with a large number of video streams, and, unlike less advanced videoconferencing systems, require intelligence for selecting adequate views for each of the connected rooms, in order to convey best what is happening in the other locations. Such a decision making component, in our implementation called Orchestration Engine (OE), acts as a Virtual Director. It processes low level events, emitted by content analysis sensors, into editing commands. The OE has two main components: one that semantically lifts low-level events into communication events and one that associates editing decisions to communication contexts. The former has to deal with uncertain and delayed information. The latter subsumes knowledge that reflects both conversation and narrative principles. Both components include contradicting bodies of knowledge. We investigate a rule-based event processing approach and reflect the scalability of our solution regarding competing and contradicting rules.
{"title":"A Rule-Based Virtual Director Enhancing Group Communication","authors":"Rene Kaiser, Wolfgang Weiss, Manolis Falelakis, Spiros Michalakopoulos, M. Ursu","doi":"10.1109/ICMEW.2012.39","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.39","url":null,"abstract":"Audiovisual group communication systems deal with a large number of video streams, and, unlike less advanced videoconferencing systems, require intelligence for selecting adequate views for each of the connected rooms, in order to convey best what is happening in the other locations. Such a decision making component, in our implementation called Orchestration Engine (OE), acts as a Virtual Director. It processes low level events, emitted by content analysis sensors, into editing commands. The OE has two main components: one that semantically lifts low-level events into communication events and one that associates editing decisions to communication contexts. The former has to deal with uncertain and delayed information. The latter subsumes knowledge that reflects both conversation and narrative principles. Both components include contradicting bodies of knowledge. We investigate a rule-based event processing approach and reflect the scalability of our solution regarding competing and contradicting rules.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114519942","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}
Jingjing Fu, Dan Miao, Weiren Yu, Shiqi Wang, Yan Lu, Shipeng Li
The Kinect-like depth compression becomes increasingly important due to the growing requirement on Kinect depth data transmission and storage. Considering the temporal inconsistency of Kinect depth introduced by the random depth measurement error, we propose 2D+T prediction algorithm aiming at fully exploiting the temporal depth correlation to enhance the Kinect depth compression efficiency. In our 2D+T prediction, each depth block is treated as a subsurface, and it the motion trend is detected by comparing with the reliable 3D reconstruction surface, which is integrated by accumulated depth information stored in depth volume. The comparison is implemented under the error tolerant rule, which is derived from the depth error model. The experimental results demonstrate our algorithm can remarkably reduce the bitrate cost and the compression complexity. And the visual quality of the 3D reconstruction results generated from our reconstructed depth is similar to that of traditional video compression algorithm.
{"title":"Kinect-Like Depth Compression with 2D+T Prediction","authors":"Jingjing Fu, Dan Miao, Weiren Yu, Shiqi Wang, Yan Lu, Shipeng Li","doi":"10.1109/ICMEW.2012.110","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.110","url":null,"abstract":"The Kinect-like depth compression becomes increasingly important due to the growing requirement on Kinect depth data transmission and storage. Considering the temporal inconsistency of Kinect depth introduced by the random depth measurement error, we propose 2D+T prediction algorithm aiming at fully exploiting the temporal depth correlation to enhance the Kinect depth compression efficiency. In our 2D+T prediction, each depth block is treated as a subsurface, and it the motion trend is detected by comparing with the reliable 3D reconstruction surface, which is integrated by accumulated depth information stored in depth volume. The comparison is implemented under the error tolerant rule, which is derived from the depth error model. The experimental results demonstrate our algorithm can remarkably reduce the bitrate cost and the compression complexity. And the visual quality of the 3D reconstruction results generated from our reconstructed depth is similar to that of traditional video compression algorithm.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115116681","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 explores how multiscale browsing can be integrated with smart phone interfaces to provide enhanced navigation through video collections. We propose a system that allows the user to interactively change the scale of the storyboards, so the user can easily adjust the amount of information provided by them. Three different methods to select key frames are studied, including an efficient method that analyzes the video and creates a scalable description, with very little computational cost. Then, storyboards of any length can be retrieved on demand without any further analysis, which is very convenient to provide fast multiscale navigation. Experimental evaluations show how this method improves the utility of the summaries and enhances user experience.
{"title":"Multiscale Browsing through Video Collections in Smartphones Using Scalable Storyboards","authors":"Luis Herranz","doi":"10.1109/ICMEW.2012.54","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.54","url":null,"abstract":"This paper explores how multiscale browsing can be integrated with smart phone interfaces to provide enhanced navigation through video collections. We propose a system that allows the user to interactively change the scale of the storyboards, so the user can easily adjust the amount of information provided by them. Three different methods to select key frames are studied, including an efficient method that analyzes the video and creates a scalable description, with very little computational cost. Then, storyboards of any length can be retrieved on demand without any further analysis, which is very convenient to provide fast multiscale navigation. Experimental evaluations show how this method improves the utility of the summaries and enhances user experience.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128235852","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}
In Mode-Dependent Directional Transform (MDDT), Karhunen-CLoeve Transform (KLT) was employed to better compress the directional edges of intra prediction residues. The transform bases of MDDT were derived from the Singular Value Decomposition (SVD) of the intra prediction residues with the diversity of video characteristics. MDDT was mode dependent, but not video content dependent. It was expected to be efficient to most video sequences. However, it did not consider the difference of video content for designing transform basis. In this paper, a video content feature is firstly defined as a concatenation of coefficient magnitude, dominant gradient and spatial activity histograms of residues. Secondly, each KLT basis which is obtained from off-line training is associated with a given feature. Thirdly, a histogram-based feature matching algorithm is proposed to select the best transform basis from the provided multiple candidates for encoding a frame. The experiments show that the average Rate-Distortion (R-D) improvement of 0.65dB PSNR can be achieved by the proposed video Content Dependent Directional Transform (CDDT) compared to the state-of-the-art MDDT for inter frame coding. Compared to Rate-Distortion Optimized Transform (RDOT), CDDT also has about 3% bits saving and comparable PSNR improvement.
{"title":"Video Content Dependent Directional Transform for High Performance Video Coding","authors":"Long Xu, K. Ngan","doi":"10.1109/ICMEW.2012.21","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.21","url":null,"abstract":"In Mode-Dependent Directional Transform (MDDT), Karhunen-CLoeve Transform (KLT) was employed to better compress the directional edges of intra prediction residues. The transform bases of MDDT were derived from the Singular Value Decomposition (SVD) of the intra prediction residues with the diversity of video characteristics. MDDT was mode dependent, but not video content dependent. It was expected to be efficient to most video sequences. However, it did not consider the difference of video content for designing transform basis. In this paper, a video content feature is firstly defined as a concatenation of coefficient magnitude, dominant gradient and spatial activity histograms of residues. Secondly, each KLT basis which is obtained from off-line training is associated with a given feature. Thirdly, a histogram-based feature matching algorithm is proposed to select the best transform basis from the provided multiple candidates for encoding a frame. The experiments show that the average Rate-Distortion (R-D) improvement of 0.65dB PSNR can be achieved by the proposed video Content Dependent Directional Transform (CDDT) compared to the state-of-the-art MDDT for inter frame coding. Compared to Rate-Distortion Optimized Transform (RDOT), CDDT also has about 3% bits saving and comparable PSNR improvement.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133827037","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}
The recent development of three dimensional (3D) display technologies has resulted in a proliferation of 3D video production and broadcasting, attracting a lot of research into capture, compression and delivery of stereoscopic content. However, the predominant design practice of interactions with 3D video content has failed to address its differences and possibilities in comparison the existing 2D video interactions. This paper presents a study of user requirements related to interaction with the stereoscopic 3D video. The study suggests that the change of view, zoom in/out, dynamic video browsing and textual information are the most relevant interactions with stereoscopic 3D video. In addition, we identified a strong demand for object selection that resulted in a follow-up study of user preferences in 3D selection using virtual-hand and ray-casting metaphors. These results indicate that interaction modality affects users' decision of object selection in terms of chosen location in 3D, while user attitudes do not have significant impact. Furthermore, the ray-casting based interaction using Wiimote can outperform the volume-based interaction technique using mouse and keyboard for object positioning accuracy.
{"title":"User Requirements Elicitation of Stereoscopic 3D Video Interaction","authors":"Haiyue Yuan, J. Calic, W. Fernando, A. Kondoz","doi":"10.1109/ICMEW.2012.13","DOIUrl":"https://doi.org/10.1109/ICMEW.2012.13","url":null,"abstract":"The recent development of three dimensional (3D) display technologies has resulted in a proliferation of 3D video production and broadcasting, attracting a lot of research into capture, compression and delivery of stereoscopic content. However, the predominant design practice of interactions with 3D video content has failed to address its differences and possibilities in comparison the existing 2D video interactions. This paper presents a study of user requirements related to interaction with the stereoscopic 3D video. The study suggests that the change of view, zoom in/out, dynamic video browsing and textual information are the most relevant interactions with stereoscopic 3D video. In addition, we identified a strong demand for object selection that resulted in a follow-up study of user preferences in 3D selection using virtual-hand and ray-casting metaphors. These results indicate that interaction modality affects users' decision of object selection in terms of chosen location in 3D, while user attitudes do not have significant impact. Furthermore, the ray-casting based interaction using Wiimote can outperform the volume-based interaction technique using mouse and keyboard for object positioning accuracy.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132885245","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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