Pub Date : 1998-01-04DOI: 10.1109/ICCV.1998.710697
G. Cross, Andrew Zisserman
We describe the recovery of a quadric surface from its image in two or more perspective views. The recovered quadric is used in 3D modeling and image registration applications. There are three novel contributions. First, it is shown that a one parameter family of quadrics is recovered from outlines in two views. The ambiguity is reduced to twofold given a point correspondence. There is no ambiguity from outlines in three or more views. Second, it is shown that degenerate quadrics reduce the ambiguity of reconstruction. Third, it is shown that surfaces can be piecewise quadric approximated from piecewise conic approximations of their outlines. All these cases are illustrated by examples with real images. Implementation details are given and the quality of the results is assessed.
{"title":"Quadric reconstruction from dual-space geometry","authors":"G. Cross, Andrew Zisserman","doi":"10.1109/ICCV.1998.710697","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710697","url":null,"abstract":"We describe the recovery of a quadric surface from its image in two or more perspective views. The recovered quadric is used in 3D modeling and image registration applications. There are three novel contributions. First, it is shown that a one parameter family of quadrics is recovered from outlines in two views. The ambiguity is reduced to twofold given a point correspondence. There is no ambiguity from outlines in three or more views. Second, it is shown that degenerate quadrics reduce the ambiguity of reconstruction. Third, it is shown that surfaces can be piecewise quadric approximated from piecewise conic approximations of their outlines. All these cases are illustrated by examples with real images. Implementation details are given and the quality of the results is assessed.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127734974","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 : 1998-01-04DOI: 10.1109/ICCV.1998.710772
C. Papageorgiou, Michael Oren, T. Poggio
This paper presents a general trainable framework for object detection in static images of cluttered scenes. The detection technique we develop is based on a wavelet representation of an object class derived from a statistical analysis of the class instances. By learning an object class in terms of a subset of an overcomplete dictionary of wavelet basis functions, we derive a compact representation of an object class which is used as an input to a support vector machine classifier. This representation overcomes both the problem of in-class variability and provides a low false detection rate in unconstrained environments. We demonstrate the capabilities of the technique in two domains whose inherent information content differs significantly. The first system is face detection and the second is the domain of people which, in contrast to faces, vary greatly in color, texture, and patterns. Unlike previous approaches, this system learns from examples and does not rely on any a priori (hand-crafted) models or motion-based segmentation. The paper also presents a motion-based extension to enhance the performance of the detection algorithm over video sequences. The results presented here suggest that this architecture may well be quite general.
{"title":"A general framework for object detection","authors":"C. Papageorgiou, Michael Oren, T. Poggio","doi":"10.1109/ICCV.1998.710772","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710772","url":null,"abstract":"This paper presents a general trainable framework for object detection in static images of cluttered scenes. The detection technique we develop is based on a wavelet representation of an object class derived from a statistical analysis of the class instances. By learning an object class in terms of a subset of an overcomplete dictionary of wavelet basis functions, we derive a compact representation of an object class which is used as an input to a support vector machine classifier. This representation overcomes both the problem of in-class variability and provides a low false detection rate in unconstrained environments. We demonstrate the capabilities of the technique in two domains whose inherent information content differs significantly. The first system is face detection and the second is the domain of people which, in contrast to faces, vary greatly in color, texture, and patterns. Unlike previous approaches, this system learns from examples and does not rely on any a priori (hand-crafted) models or motion-based segmentation. The paper also presents a motion-based extension to enhance the performance of the detection algorithm over video sequences. The results presented here suggest that this architecture may well be quite general.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122256392","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 : 1998-01-04DOI: 10.1109/ICCV.1998.710824
N. Ferrier
In order to take advantage of the top speed of manipulators, vision cannot be tightly integrated into the motion control loop. Past visual servo control systems have performed satisfactorily with this constraint, however it can be shown that the task execution time can be reduced if the vision system is de-coupled from the low level motor control system. For reaching, there is a trade-off between the accuracy of a motion and the time required to execute motion. In studies of human motor control this tradeoff is quantified by Fitts Law, a relationship between the motion time, the target distance, and the target width. These studies suggest that vision is not used tightly within the control loop, i.e. as a sensor that is servo-ed on, but rather vision is used to determine where the reaching target is and whether target has been reached successfully. Through a simple robotic example we demonstrate that a similar trade off exists between motion accuracy and the motion execution time for visual guided robot reaching motions.
{"title":"Achieving a Fitts law relationship for visual guided reaching","authors":"N. Ferrier","doi":"10.1109/ICCV.1998.710824","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710824","url":null,"abstract":"In order to take advantage of the top speed of manipulators, vision cannot be tightly integrated into the motion control loop. Past visual servo control systems have performed satisfactorily with this constraint, however it can be shown that the task execution time can be reduced if the vision system is de-coupled from the low level motor control system. For reaching, there is a trade-off between the accuracy of a motion and the time required to execute motion. In studies of human motor control this tradeoff is quantified by Fitts Law, a relationship between the motion time, the target distance, and the target width. These studies suggest that vision is not used tightly within the control loop, i.e. as a sensor that is servo-ed on, but rather vision is used to determine where the reaching target is and whether target has been reached successfully. Through a simple robotic example we demonstrate that a similar trade off exists between motion accuracy and the motion execution time for visual guided robot reaching motions.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130166805","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 : 1998-01-04DOI: 10.1109/ICCV.1998.710711
H. Schweitzer
Ritz vectors approximate eigenvectors that are a common choice for primary images in content based indexing. They can be computed efficiently even when the images are accessed through slow communication such as the Internet. We develop an algorithm that computes Ritz vectors in one pass through the images. When iterated, the algorithm can recover the exact eigenvectors. In applications to image indexing and learning it may be necessary to compute primary images for indexing many sub-categories of the image set. The proposed algorithm can compute these age data. Similar computation by other algorithms is much more costly even when access to the images is inexpensive.
{"title":"Computing Ritz approximations of primary images","authors":"H. Schweitzer","doi":"10.1109/ICCV.1998.710711","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710711","url":null,"abstract":"Ritz vectors approximate eigenvectors that are a common choice for primary images in content based indexing. They can be computed efficiently even when the images are accessed through slow communication such as the Internet. We develop an algorithm that computes Ritz vectors in one pass through the images. When iterated, the algorithm can recover the exact eigenvectors. In applications to image indexing and learning it may be necessary to compute primary images for indexing many sub-categories of the image set. The proposed algorithm can compute these age data. Similar computation by other algorithms is much more costly even when access to the images is inexpensive.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"363 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134262222","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 : 1998-01-04DOI: 10.1109/ICCV.1998.710838
J. Gluckman, S. Nayar
Recent research in image sensors has produced cameras with very large fields of view. An area of computer vision research which will benefit from this technology is the computation of camera motion (ego-motion) from a sequence of images. Traditional cameras stiffer from the problem that the direction of translation may lie outside of the field of view, making the computation of camera motion sensitive to noise. In this paper, we present a method for the recovery of ego-motion using omnidirectional cameras. Noting the relationship between spherical projection and wide-angle imaging devices, we propose mapping the image velocity vectors to a sphere, using the Jacobian of the transformation between the projection model of the camera and spherical projection. Once the velocity vectors are mapped to a sphere, we show how existing ego-motion algorithms can be applied and present some experimental results. These results demonstrate the ability to compute ego-motion with omnidirectional cameras.
{"title":"Ego-motion and omnidirectional cameras","authors":"J. Gluckman, S. Nayar","doi":"10.1109/ICCV.1998.710838","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710838","url":null,"abstract":"Recent research in image sensors has produced cameras with very large fields of view. An area of computer vision research which will benefit from this technology is the computation of camera motion (ego-motion) from a sequence of images. Traditional cameras stiffer from the problem that the direction of translation may lie outside of the field of view, making the computation of camera motion sensitive to noise. In this paper, we present a method for the recovery of ego-motion using omnidirectional cameras. Noting the relationship between spherical projection and wide-angle imaging devices, we propose mapping the image velocity vectors to a sphere, using the Jacobian of the transformation between the projection model of the camera and spherical projection. Once the velocity vectors are mapped to a sphere, we show how existing ego-motion algorithms can be applied and present some experimental results. These results demonstrate the ability to compute ego-motion with omnidirectional cameras.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130719713","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 : 1998-01-04DOI: 10.1109/ICCV.1998.710746
Fang Liu, Rosalind W. Picard
An algorithm for simultaneous detection, segmentation, and characterization of spatiotemporal periodicity is presented. The use of periodicity templates is proposed to localize and characterize temporal activities. The templates not only indicate the presence and location of a periodic event, but also give an accurate quantitative periodicity measure. Hence, they can be used as a new means of periodicity representation. The proposed algorithm can also be considered as a "periodicity filter", a low-level model of periodicity perception. The algorithm is computationally simple, and shown to be more robust than optical flow based techniques in the presence of noise. A variety of real-world examples are used to demonstrate the performance of the algorithm.
{"title":"Finding periodicity in space and time","authors":"Fang Liu, Rosalind W. Picard","doi":"10.1109/ICCV.1998.710746","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710746","url":null,"abstract":"An algorithm for simultaneous detection, segmentation, and characterization of spatiotemporal periodicity is presented. The use of periodicity templates is proposed to localize and characterize temporal activities. The templates not only indicate the presence and location of a periodic event, but also give an accurate quantitative periodicity measure. Hence, they can be used as a new means of periodicity representation. The proposed algorithm can also be considered as a \"periodicity filter\", a low-level model of periodicity perception. The algorithm is computationally simple, and shown to be more robust than optical flow based techniques in the presence of noise. A variety of real-world examples are used to demonstrate the performance of the algorithm.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132849296","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 : 1998-01-04DOI: 10.1109/ICCV.1998.710786
S. Gutta, Jeffrey R. Huang, Vishal Kakkad, H. Wechsler
Most of the research on face recognition addresses the MATCH problem and it assumes a closed universe where there is no need for a REJECT ('false positive') option. The SURVEILLANCE problem is addressed indirectly, if at all, through the MATCH problem, where the size of the gallery rather than that of the probe set is very large. This paper addresses the proper surveillance problem where the size of the probe ('unknown image') set vs. gallery ('known image') set is 450 vs. 50 frontal images. We developed robust face ID verification ('classification') and retrieval schemes based on hybrid classifiers and showed their feasibility using the FERET face data base. The hybrid classifier architecture consists of an ensemble of connectionist networks-Radial Basis Functions (RBF) and inductive decision trees (DT). Experimental results prove the feasibility of our approach and yield 97% accuracy using the probe and gallery sets specified above.
{"title":"Face surveillance","authors":"S. Gutta, Jeffrey R. Huang, Vishal Kakkad, H. Wechsler","doi":"10.1109/ICCV.1998.710786","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710786","url":null,"abstract":"Most of the research on face recognition addresses the MATCH problem and it assumes a closed universe where there is no need for a REJECT ('false positive') option. The SURVEILLANCE problem is addressed indirectly, if at all, through the MATCH problem, where the size of the gallery rather than that of the probe set is very large. This paper addresses the proper surveillance problem where the size of the probe ('unknown image') set vs. gallery ('known image') set is 450 vs. 50 frontal images. We developed robust face ID verification ('classification') and retrieval schemes based on hybrid classifiers and showed their feasibility using the FERET face data base. The hybrid classifier architecture consists of an ensemble of connectionist networks-Radial Basis Functions (RBF) and inductive decision trees (DT). Experimental results prove the feasibility of our approach and yield 97% accuracy using the probe and gallery sets specified above.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"48 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132895054","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 : 1998-01-04DOI: 10.1109/ICCV.1998.710694
P J Narayanan, P. Rander, T. Kanade
We present Virtualized Reality, a technique to create virtual worlds out of dynamic events using densely distributed stereo views. The intensity image and depth map for each camera view at each time instant are combined to form a Visible Surface Model. Immersive interaction with the virtualized event is possible using a dense collection of such models. Additionally, a Complete Surface Model of each instant can be built by merging the depth maps from different cameras into a common volumetric space. The corresponding model is compatible with traditional virtual models and can be interacted with immersively using standard tools. Because both VSMs and CSMs are fully three-dimensional, virtualized models can also be combined and modified to build larger, more complex environments, an important capability for many non-trivial applications. We present results from 3D Dome, our facility to create virtualized models.
{"title":"Constructing virtual worlds using dense stereo","authors":"P J Narayanan, P. Rander, T. Kanade","doi":"10.1109/ICCV.1998.710694","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710694","url":null,"abstract":"We present Virtualized Reality, a technique to create virtual worlds out of dynamic events using densely distributed stereo views. The intensity image and depth map for each camera view at each time instant are combined to form a Visible Surface Model. Immersive interaction with the virtualized event is possible using a dense collection of such models. Additionally, a Complete Surface Model of each instant can be built by merging the depth maps from different cameras into a common volumetric space. The corresponding model is compatible with traditional virtual models and can be interacted with immersively using standard tools. Because both VSMs and CSMs are fully three-dimensional, virtualized models can also be combined and modified to build larger, more complex environments, an important capability for many non-trivial applications. We present results from 3D Dome, our facility to create virtualized models.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124181895","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 : 1998-01-04DOI: 10.1109/ICCV.1998.710795
Jorge Batista, Helder Sabino de Araújo, A. T. Almeida
Perspective camera calibration has been in the last decades a research subject for a large group of researchers and as a result several camera calibration methodologies can be found in the literature. However only a small number of those methods base their approaches on the use of monoplane calibration points. This paper describes one of those methodologies that uses monoplane calibration points to realize an explicit 3D camera calibration. To avoid the singularity obtained with the calibration equations when monoplane calibration points are used, this method computes the calibration parameters in a multi-step procedure and requires a first-guess solution for the intrinsic parameters. These parameters are updated and their accuracy increased through an iterative procedure. A stability analysis as a function of the pose of the camera is presented. Camera pose view strategies for accurate camera orientation computation can be extracted from the pose view stability analysis.
{"title":"Iterative multi-step explicit camera calibration","authors":"Jorge Batista, Helder Sabino de Araújo, A. T. Almeida","doi":"10.1109/ICCV.1998.710795","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710795","url":null,"abstract":"Perspective camera calibration has been in the last decades a research subject for a large group of researchers and as a result several camera calibration methodologies can be found in the literature. However only a small number of those methods base their approaches on the use of monoplane calibration points. This paper describes one of those methodologies that uses monoplane calibration points to realize an explicit 3D camera calibration. To avoid the singularity obtained with the calibration equations when monoplane calibration points are used, this method computes the calibration parameters in a multi-step procedure and requires a first-guess solution for the intrinsic parameters. These parameters are updated and their accuracy increased through an iterative procedure. A stability analysis as a function of the pose of the camera is presented. Camera pose view strategies for accurate camera orientation computation can be extracted from the pose view stability analysis.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125830564","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 : 1998-01-04DOI: 10.1109/ICCV.1998.710857
S. Tari, J. Shah
Motivated by a need to define an object-centered reference system determined by the most salient characteristics of the shape, many methods have been proposed, all of which directly or indirectly involve an axis about which the shape is locally symmetric. Recently, a function /spl upsi/, called "the edge strength function", has been successfully used to determine efficiently the axes of local symmetries of 2-d shapes. The level curves of /spl upsi/ are interpreted as successively smoother versions of the initial shape boundary. The local minima of the absolute gradient /spl par//spl nabla//spl upsi//spl par/ along the level curves of /spl upsi/ are shown to be a robust criterion for determining the shape skeleton. More generally, at an extremal point of /spl par//spl nabla//spl upsi//spl par/ along a level curve, the level curve is locally symmetric with respect to the gradient vector /spl nabla//spl upsi/. That is, at such a point, the level curve is approximately a conic section whose one of the principal axes coincides with the gradient vector. Thus, the locus of the extremal points of /spl par//spl nabla//spl upsi//spl par/ along the level curves determines the axes of local symmetries of the shape. In this paper, we extend this method to shapes of arbitrary dimension.
{"title":"Local symmetries of shapes in arbitrary dimension","authors":"S. Tari, J. Shah","doi":"10.1109/ICCV.1998.710857","DOIUrl":"https://doi.org/10.1109/ICCV.1998.710857","url":null,"abstract":"Motivated by a need to define an object-centered reference system determined by the most salient characteristics of the shape, many methods have been proposed, all of which directly or indirectly involve an axis about which the shape is locally symmetric. Recently, a function /spl upsi/, called \"the edge strength function\", has been successfully used to determine efficiently the axes of local symmetries of 2-d shapes. The level curves of /spl upsi/ are interpreted as successively smoother versions of the initial shape boundary. The local minima of the absolute gradient /spl par//spl nabla//spl upsi//spl par/ along the level curves of /spl upsi/ are shown to be a robust criterion for determining the shape skeleton. More generally, at an extremal point of /spl par//spl nabla//spl upsi//spl par/ along a level curve, the level curve is locally symmetric with respect to the gradient vector /spl nabla//spl upsi/. That is, at such a point, the level curve is approximately a conic section whose one of the principal axes coincides with the gradient vector. Thus, the locus of the extremal points of /spl par//spl nabla//spl upsi//spl par/ along the level curves determines the axes of local symmetries of the shape. In this paper, we extend this method to shapes of arbitrary dimension.","PeriodicalId":270671,"journal":{"name":"Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124780905","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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