Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611890
Yuan Xu, Qinghai Zhou, Liwei Gong, Mingcheng Zhu, Robert K. F. Teng
This paper presents a method of real-time panoramic video system implemented by using FPGA. In order to meet the real-time and high-resolution requirements, a novel method based on pipeline CORDIC and look-up tables for simultaneous image transformations, such as lens distortion correction, perspective transformation and image cylinder projection has been developed. Taking the advantages of the high speed parallel architecture of FPGA and the developed novel algorithm modules, a real-time, low latency and high-performance panoramic video has been studied and developed. The video system presented in this paper could generate panoramic video of 5*1280(H)*720(V) @15FPS or 5*1280(H)*360(V) @30FPS in real-time. In order to display the panoramic video, a display module that can output the panoramic video in slide mode has also been built.
{"title":"Study of a FPGA real-time multi-cameras cylindrical panorama video system with low latency and high performance","authors":"Yuan Xu, Qinghai Zhou, Liwei Gong, Mingcheng Zhu, Robert K. F. Teng","doi":"10.1109/IVMSPW.2013.6611890","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611890","url":null,"abstract":"This paper presents a method of real-time panoramic video system implemented by using FPGA. In order to meet the real-time and high-resolution requirements, a novel method based on pipeline CORDIC and look-up tables for simultaneous image transformations, such as lens distortion correction, perspective transformation and image cylinder projection has been developed. Taking the advantages of the high speed parallel architecture of FPGA and the developed novel algorithm modules, a real-time, low latency and high-performance panoramic video has been studied and developed. The video system presented in this paper could generate panoramic video of 5*1280(H)*720(V) @15FPS or 5*1280(H)*360(V) @30FPS in real-time. In order to display the panoramic video, a display module that can output the panoramic video in slide mode has also been built.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127041987","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}
Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611905
Pierre R. Lebreton, A. Raake, M. Barkowsky, P. Callet
3D video quality of experience (QoE) is a multidimensional problem and many factors contribute to the global experience by the user. Due to this multidimensionality, this paper evaluates the integral 3D video QoE and relates it with image quality and depth. Subjective tests have been conducted using paired comparison to evaluate 3D QoE and the preference of 3D over 2D with different combinations of coding conditions. Depth scores were available from previous work and were used to check their relation with 3DQoE; the difference between 2D and 3D QoE is found to be a function of the picture quality, and the desired preference of 3D presentation over 2D can be reached when pictorial quality is high enough (VQM score lower than 0.24). A factor ranging from 0.08 to 0.76 with a mean of 0.71 between pictorial quality and preference of 3D was also found.
{"title":"Perceptual preference of S3D over 2D for HDTV in dependence of video quality and depth","authors":"Pierre R. Lebreton, A. Raake, M. Barkowsky, P. Callet","doi":"10.1109/IVMSPW.2013.6611905","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611905","url":null,"abstract":"3D video quality of experience (QoE) is a multidimensional problem and many factors contribute to the global experience by the user. Due to this multidimensionality, this paper evaluates the integral 3D video QoE and relates it with image quality and depth. Subjective tests have been conducted using paired comparison to evaluate 3D QoE and the preference of 3D over 2D with different combinations of coding conditions. Depth scores were available from previous work and were used to check their relation with 3DQoE; the difference between 2D and 3D QoE is found to be a function of the picture quality, and the desired preference of 3D presentation over 2D can be reached when pictorial quality is high enough (VQM score lower than 0.24). A factor ranging from 0.08 to 0.76 with a mean of 0.71 between pictorial quality and preference of 3D was also found.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125750897","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}
Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611931
Alexandros Iosifidis, A. Tefas, I. Pitas
In this paper a novel view-independent human action recognition method is proposed. A multi-camera setup is used to capture the human body from different viewing angles. Actions are described by a novel action representation, the so-called multi-view action image (MVAI), which effectively addresses the camera viewpoint identification problem, i.e., the identification of the position of each camera with respect to the person's body. Linear Discriminant Analysis is applied on the MVAIs in order to to map actions to a discriminant feature space where actions are classified by using a simple nearest class centroid classification scheme. Experimental results denote the effectiveness of the proposed action recognition approach.
{"title":"View-independent human action recognition based on multi-view action images and discriminant learning","authors":"Alexandros Iosifidis, A. Tefas, I. Pitas","doi":"10.1109/IVMSPW.2013.6611931","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611931","url":null,"abstract":"In this paper a novel view-independent human action recognition method is proposed. A multi-camera setup is used to capture the human body from different viewing angles. Actions are described by a novel action representation, the so-called multi-view action image (MVAI), which effectively addresses the camera viewpoint identification problem, i.e., the identification of the position of each camera with respect to the person's body. Linear Discriminant Analysis is applied on the MVAIs in order to to map actions to a discriminant feature space where actions are classified by using a simple nearest class centroid classification scheme. Experimental results denote the effectiveness of the proposed action recognition approach.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134087718","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}
Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611903
Zhi Jin, T. Tillo, Jimin Xiao, Fei Cheng
Depth map based 3-D view synthesis technique allows to synthesize different virtual perspectives of the same 3-D content, and the lifelike 3-D view perception of these virtual perspectives is highly depending on the accuracy of depth information. So, although depth map is not viewed by the users, however, its quality directly affects that of the synthesized virtual views by the 3-D warping process. In view of current progress in depth map acquisition techniques, and in order to maintain compatibility with different encoding standards depth values need to undergo quantization, so as to be represented at practical and convenient values. However, the quantization process causes depth map distortion. In order to reduce this negative effect, this paper propose a new quantization method which jointly considers the distribution of depth values and the 3-D rendering process, so as to minimize the depth map induced rendering distortion. The experimental results with the proposed quantization method indicate that the SNR gain has increased from 1dB to 14dB for different sequences when compared with the traditional non-uniform quantization method.
{"title":"3-D video depth map quantization based on Lloyd's algorithm","authors":"Zhi Jin, T. Tillo, Jimin Xiao, Fei Cheng","doi":"10.1109/IVMSPW.2013.6611903","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611903","url":null,"abstract":"Depth map based 3-D view synthesis technique allows to synthesize different virtual perspectives of the same 3-D content, and the lifelike 3-D view perception of these virtual perspectives is highly depending on the accuracy of depth information. So, although depth map is not viewed by the users, however, its quality directly affects that of the synthesized virtual views by the 3-D warping process. In view of current progress in depth map acquisition techniques, and in order to maintain compatibility with different encoding standards depth values need to undergo quantization, so as to be represented at practical and convenient values. However, the quantization process causes depth map distortion. In order to reduce this negative effect, this paper propose a new quantization method which jointly considers the distribution of depth values and the 3-D rendering process, so as to minimize the depth map induced rendering distortion. The experimental results with the proposed quantization method indicate that the SNR gain has increased from 1dB to 14dB for different sequences when compared with the traditional non-uniform quantization method.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116218544","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}
Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611897
Yeejin Lee, Zucheul Lee, Truong Q. Nguyen
This paper presents a new frame-rate up conversion method for video plus depth representation. The proposed method improves the quality of video using additional depth information. The depth information is utilized in three ways to improve the accuracy of motion estimation. One usage is that depth frame is added in block matching criterion to estimate initial motion. Another usage is to detect object boundary region combining depth value variation and local depth distribution adjustment technique. Finally, motion vector field is refined adaptively by segmenting macroblocks into object regions. Any existing block-based motion-compensated frame interpolation methods may utilize our method to refine motion vector field by using depth frames. Experimental results verify that the proposed method outperforms the conventional motion-compensated frame interpolation algorithms, while preserving object structure.
{"title":"Frame rate up conversion of 3D video by motion and depth fusion","authors":"Yeejin Lee, Zucheul Lee, Truong Q. Nguyen","doi":"10.1109/IVMSPW.2013.6611897","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611897","url":null,"abstract":"This paper presents a new frame-rate up conversion method for video plus depth representation. The proposed method improves the quality of video using additional depth information. The depth information is utilized in three ways to improve the accuracy of motion estimation. One usage is that depth frame is added in block matching criterion to estimate initial motion. Another usage is to detect object boundary region combining depth value variation and local depth distribution adjustment technique. Finally, motion vector field is refined adaptively by segmenting macroblocks into object regions. Any existing block-based motion-compensated frame interpolation methods may utilize our method to refine motion vector field by using depth frames. Experimental results verify that the proposed method outperforms the conventional motion-compensated frame interpolation algorithms, while preserving object structure.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134404780","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}
Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611936
Hyunsuk Ko, Chang-Su Kim, S. Choi, C.-C. Jay Kuo
A novel quality index for stereoscopic image pairs is proposed in this work. First, we introduce a parameter called the structural distortion parameter (SDP), which varies according to different distortion types. Then, we use the SDP as a control parameter in a binocular perception model, and apply it into three components of SSIM to obtain an overall quality index. In the proposed framework, the binocular model accommodates distortion types and distortion degrees and, therefore, offers robust quality assessment results for both symmetric and asymmetric distortions. It is shown by experimental results that the proposed index outperforms several existing 3D image quality index methods.
{"title":"3D image quality index using SDP-based binocular perception model","authors":"Hyunsuk Ko, Chang-Su Kim, S. Choi, C.-C. Jay Kuo","doi":"10.1109/IVMSPW.2013.6611936","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611936","url":null,"abstract":"A novel quality index for stereoscopic image pairs is proposed in this work. First, we introduce a parameter called the structural distortion parameter (SDP), which varies according to different distortion types. Then, we use the SDP as a control parameter in a binocular perception model, and apply it into three components of SSIM to obtain an overall quality index. In the proposed framework, the binocular model accommodates distortion types and distortion degrees and, therefore, offers robust quality assessment results for both symmetric and asymmetric distortions. It is shown by experimental results that the proposed index outperforms several existing 3D image quality index methods.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122682266","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}
Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611934
Weicheng Huang, Xun Cao, K. Lu, Qionghai Dai, A. Bovik
We propose a two-stage depth propagation algorithm for semi-automatic 2D-to-3D video conversion that forces the solution towards statistical “naturalness”. First, both forward and backward motion vectors are estimated and compared to decide initial depth values, then a compensation process is adopted to further improve the depth initialization. Secondly, the luminance and initial depth are decomposed into a wavelet pyramid. Each sub-band of depth is inferred using a Bayesian formulation under a natural scene statistic prior assumption. This is incorporated into a propagation target function as a prior regularizing term. The final depth map associated with each frame of the input 2D video is optimized by composing all the sub-bands. Experimental results obtained on various sequences show that the presented method outperforms several state-of-the-art depth propagation methods.
{"title":"Towards naturalistic depth propagation","authors":"Weicheng Huang, Xun Cao, K. Lu, Qionghai Dai, A. Bovik","doi":"10.1109/IVMSPW.2013.6611934","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611934","url":null,"abstract":"We propose a two-stage depth propagation algorithm for semi-automatic 2D-to-3D video conversion that forces the solution towards statistical “naturalness”. First, both forward and backward motion vectors are estimated and compared to decide initial depth values, then a compensation process is adopted to further improve the depth initialization. Secondly, the luminance and initial depth are decomposed into a wavelet pyramid. Each sub-band of depth is inferred using a Bayesian formulation under a natural scene statistic prior assumption. This is incorporated into a propagation target function as a prior regularizing term. The final depth map associated with each frame of the input 2D video is optimized by composing all the sub-bands. Experimental results obtained on various sequences show that the presented method outperforms several state-of-the-art depth propagation methods.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130688454","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}
Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611896
S. Woolford, I. Burnett
In this paper a new method of determining 3D object shape using patterns derived from Direct Sequence Spread Spectrum (DSSS) and an Unscented Kalman Filter (UKF) is presented. First a binary message is encoded via Binary Phase Shift Keying (BPSK), and spread using pseudo-random spreading to create a pattern. An Iterative Unscented Kalman Filter (IUKF) is then used to determine the deformation in the pattern due to an object, and a Kalman smoother is used to reduce noise in the deformation estimation. Results show that the iterative UKF is able to determine the deformation in the pattern with a lower absolute error residual between the ground truth and estimated deformation than the non-iterated UKF. Results of the accompanying Cramer-Rao lower bounds show that the lower bound on the DSSS Pattern is lower than that of the fringe pattern.
{"title":"A novel one shot object profilometry system using Direct Sequence Spread Spectrum profilometry","authors":"S. Woolford, I. Burnett","doi":"10.1109/IVMSPW.2013.6611896","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611896","url":null,"abstract":"In this paper a new method of determining 3D object shape using patterns derived from Direct Sequence Spread Spectrum (DSSS) and an Unscented Kalman Filter (UKF) is presented. First a binary message is encoded via Binary Phase Shift Keying (BPSK), and spread using pseudo-random spreading to create a pattern. An Iterative Unscented Kalman Filter (IUKF) is then used to determine the deformation in the pattern due to an object, and a Kalman smoother is used to reduce noise in the deformation estimation. Results show that the iterative UKF is able to determine the deformation in the pattern with a lower absolute error residual between the ground truth and estimated deformation than the non-iterated UKF. Results of the accompanying Cramer-Rao lower bounds show that the lower bound on the DSSS Pattern is lower than that of the fringe pattern.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121618541","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}
Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611938
Yixian Liu, Xinyu Lin, Qianni Zhang, E. Izquierdo
Interpreting 3D structure from 2D images is a constant problem to be solved in the field of computer vision. Prior work has been made to tackle this issue mainly in two different ways - depth estimation from multiple-view images based on geometric triangulation and depth reasoning from single image depending on monocular depth cues. Both solutions do not involve direct depth map information. In this work, we captured a RGBD dataset using Microsoft Kinect depth sensor. Approximate depth information is acquired as the fourth channel and employed as an extra reference for 3D scene geometry reasoning. It helps to achieve better estimation accuracy. We define nine basic geometric models for general indoor restricted-view scenes. Then we extract low/medium level colour and depth features from all four of the RGBD channels. Sequential Minimal Optimization SVM is used in this work as efficient classification tool. Experiments are implemented to compare the result of this approach with previous work that does not have the depth channel as input.
{"title":"Improved indoor scene geometry recognition from single image based on depth map","authors":"Yixian Liu, Xinyu Lin, Qianni Zhang, E. Izquierdo","doi":"10.1109/IVMSPW.2013.6611938","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611938","url":null,"abstract":"Interpreting 3D structure from 2D images is a constant problem to be solved in the field of computer vision. Prior work has been made to tackle this issue mainly in two different ways - depth estimation from multiple-view images based on geometric triangulation and depth reasoning from single image depending on monocular depth cues. Both solutions do not involve direct depth map information. In this work, we captured a RGBD dataset using Microsoft Kinect depth sensor. Approximate depth information is acquired as the fourth channel and employed as an extra reference for 3D scene geometry reasoning. It helps to achieve better estimation accuracy. We define nine basic geometric models for general indoor restricted-view scenes. Then we extract low/medium level colour and depth features from all four of the RGBD channels. Sequential Minimal Optimization SVM is used in this work as efficient classification tool. Experiments are implemented to compare the result of this approach with previous work that does not have the depth channel as input.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"308 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129750645","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}
Pub Date : 2013-06-10DOI: 10.1109/IVMSPW.2013.6611940
M. Mahmood
Usually, in Shape From Focus (SFF) methods, a single focus measure is applied on an image sequence to obtain an initial depth map and then an approximation technique is used to recover three-dimensional (3D) shape of an object. However, different focus measures perform differently in diverse conditions and it is hard to get accurate 3D shape based on a single focus measure. In this paper, we propose a nonlinear Total Variation (TV) based method for recovering 3D shape of an object by diffusing several initial depth maps obtained through different focus measures. Several experiments have been conducted using images of synthetic and real objects to evaluate the performance of the proposed method. Comparative analysis demonstrates of the effectiveness of the proposed approach.
形状从焦点(Shape From Focus, SFF)方法通常是对图像序列进行单焦点测量获得初始深度图，然后使用近似技术恢复物体的三维形状。然而，不同的焦距测量在不同的条件下表现不同，基于单一的焦距测量很难获得准确的三维形状。本文提出了一种基于非线性全变分(TV)的方法，通过对不同焦点测量得到的多个初始深度图进行扩散来恢复物体的三维形状。利用合成物体和真实物体的图像进行了多次实验，以评估所提出方法的性能。对比分析表明了该方法的有效性。
{"title":"Shape From Focus by Total Variation","authors":"M. Mahmood","doi":"10.1109/IVMSPW.2013.6611940","DOIUrl":"https://doi.org/10.1109/IVMSPW.2013.6611940","url":null,"abstract":"Usually, in Shape From Focus (SFF) methods, a single focus measure is applied on an image sequence to obtain an initial depth map and then an approximation technique is used to recover three-dimensional (3D) shape of an object. However, different focus measures perform differently in diverse conditions and it is hard to get accurate 3D shape based on a single focus measure. In this paper, we propose a nonlinear Total Variation (TV) based method for recovering 3D shape of an object by diffusing several initial depth maps obtained through different focus measures. Several experiments have been conducted using images of synthetic and real objects to evaluate the performance of the proposed method. Comparative analysis demonstrates of the effectiveness of the proposed approach.","PeriodicalId":170714,"journal":{"name":"IVMSP 2013","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133214272","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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