Pub Date : 2004-06-14DOI: 10.1109/IVS.2004.1336362
T. D’orazio, M. Leo, A. Distante
For a driver vigilance system one of the most important problems to be solved is eye detection. In this paper, we propose a new algorithm for eye detection that uses both iris geometrical information for determining in the whole image, the region candidate to contain an eye, and the symmetry for selecting the couple of eyes. The novelty of this work is that the algorithm works on complex images without constraints on the background, skin color segmentation and so on. After the first step, a validation algorithm based on a neural classifier has been applied to recognize if the couple of regions correspond effectively to eyes or false positives have been detected. Different experiments have been carried out on images of subjects with different eye colours, some of them wearing glasses. Tests showed robustness with respect to situations such as eyes partially occluded. In particular when applied to images where people have the eyes closed, the proposed algorithm correctly reveals the absence of eyes.
{"title":"Eye detection in face images for a driver vigilance system","authors":"T. D’orazio, M. Leo, A. Distante","doi":"10.1109/IVS.2004.1336362","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336362","url":null,"abstract":"For a driver vigilance system one of the most important problems to be solved is eye detection. In this paper, we propose a new algorithm for eye detection that uses both iris geometrical information for determining in the whole image, the region candidate to contain an eye, and the symmetry for selecting the couple of eyes. The novelty of this work is that the algorithm works on complex images without constraints on the background, skin color segmentation and so on. After the first step, a validation algorithm based on a neural classifier has been applied to recognize if the couple of regions correspond effectively to eyes or false positives have been detected. Different experiments have been carried out on images of subjects with different eye colours, some of them wearing glasses. Tests showed robustness with respect to situations such as eyes partially occluded. In particular when applied to images where people have the eyes closed, the proposed algorithm correctly reveals the absence of eyes.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"306 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117188045","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 : 2004-06-14DOI: 10.1109/IVS.2004.1336439
Cédric Demonceaux, D. Kachi-Akkouche
This paper deals with the problem of obstacle detection from a single camera mounted on a vehicle. We define an obstacle as any object that obstructs the vehicle's driving path. The perception of the environment is performed through a fast processing of image sequence. The approach is based on motion analysis. Generally, the optical flow techniques are huge in computation time and sensitive to vehicle motion. To overcome these problems, we choose to detect the obstacle in two steps. The road motion is firstly computed through a fast and robust wavelets analysis. Then, we detect the areas which have a different motion thanks to a Bayesian modelization. Results shown in the paper prove that the proposed method permits the detection of any obstacle on a road.
{"title":"Robust obstacle detection with monocular vision based on motion analysis","authors":"Cédric Demonceaux, D. Kachi-Akkouche","doi":"10.1109/IVS.2004.1336439","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336439","url":null,"abstract":"This paper deals with the problem of obstacle detection from a single camera mounted on a vehicle. We define an obstacle as any object that obstructs the vehicle's driving path. The perception of the environment is performed through a fast processing of image sequence. The approach is based on motion analysis. Generally, the optical flow techniques are huge in computation time and sensitive to vehicle motion. To overcome these problems, we choose to detect the obstacle in two steps. The road motion is firstly computed through a fast and robust wavelets analysis. Then, we detect the areas which have a different motion thanks to a Bayesian modelization. Results shown in the paper prove that the proposed method permits the detection of any obstacle on a road.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121056882","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 : 2004-06-14DOI: 10.1109/IVS.2004.1336400
A. Broggi, Pietro Cerri, P. C. Antonello
This paper describes a vehicle detection system using a single camera. It is based on the search for areas with a high vertical symmetry in multi-resolution images; symmetry is computed using different sized boxes centered on all the columns of the interest areas. All the columns with high symmetry are analyzed to get the width of detected objects. Horizontal edges are examined to find the base of the vehicle in the individuated area. The aim is to find horizontal lines located below an area with sufficient amount of edges. The algorithm deletes all the bounding boxes which are too large, too small, or too far from the camera in order to decrease the number of false positives. All the results found in different interest areas are mixed together and the overlapping bounding boxes are localized and managed in order to delete false positives. The algorithm analyzes images on a frame by frame basis, without any temporal correlation.
{"title":"Multi-resolution vehicle detection using artificial vision","authors":"A. Broggi, Pietro Cerri, P. C. Antonello","doi":"10.1109/IVS.2004.1336400","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336400","url":null,"abstract":"This paper describes a vehicle detection system using a single camera. It is based on the search for areas with a high vertical symmetry in multi-resolution images; symmetry is computed using different sized boxes centered on all the columns of the interest areas. All the columns with high symmetry are analyzed to get the width of detected objects. Horizontal edges are examined to find the base of the vehicle in the individuated area. The aim is to find horizontal lines located below an area with sufficient amount of edges. The algorithm deletes all the bounding boxes which are too large, too small, or too far from the camera in order to decrease the number of false positives. All the results found in different interest areas are mixed together and the overlapping bounding boxes are localized and managed in order to delete false positives. The algorithm analyzes images on a frame by frame basis, without any temporal correlation.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127544595","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 : 2004-06-14DOI: 10.1109/IVS.2004.1336365
T. Nagaosa, Y. Kobayashi, K. Mori, H. Kobayashi
We examine the performance of inter-vehicle communication (IVC) systems using the IEEE802.11b standard CSMA scheme and a proposed system in which packet transmission timing is decided by the vehicle position. For the realization of safety cruise-assist systems by IVC systems, the spread of transceivers on vehicles is important. To improve the equipped rate of transceivers on vehicles, it is necessary that the implementation of more simple and cheaper IVC systems. One of the solutions is using conventional wireless LAN systems for IVC systems. So we evaluate the performance of an IVC system using the conventional IEEE802.11b CSMA system. In addition, we propose and evaluate an improvement scheme for solving the performance degradation caused by packet collision. The results of simulation show that the proposed scheme is superior to other schemes when the bit rate is low. Also, it is shown that the proposed scheme has the same or higher performance than the other schemes in high bit rate.
{"title":"An advanced CSMA inter-vehicle communication system using packet transmission timing decided by the vehicle position","authors":"T. Nagaosa, Y. Kobayashi, K. Mori, H. Kobayashi","doi":"10.1109/IVS.2004.1336365","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336365","url":null,"abstract":"We examine the performance of inter-vehicle communication (IVC) systems using the IEEE802.11b standard CSMA scheme and a proposed system in which packet transmission timing is decided by the vehicle position. For the realization of safety cruise-assist systems by IVC systems, the spread of transceivers on vehicles is important. To improve the equipped rate of transceivers on vehicles, it is necessary that the implementation of more simple and cheaper IVC systems. One of the solutions is using conventional wireless LAN systems for IVC systems. So we evaluate the performance of an IVC system using the conventional IEEE802.11b CSMA system. In addition, we propose and evaluate an improvement scheme for solving the performance degradation caused by packet collision. The results of simulation show that the proposed scheme is superior to other schemes when the bit rate is low. Also, it is shown that the proposed scheme has the same or higher performance than the other schemes in high bit rate.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125892866","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 : 2004-06-14DOI: 10.1109/IVS.2004.1336443
B. Fardi, G. Wanielik
This paper describes a real-time image processing algorithm for road border detection in infrared images. The basic idea is to couple the road border lines through the parallelism between them in the vehicle coordinate system. The parallelism of the two lines is translated in their convergence in the image plane due to the perspective projection. In this plane the two lines meet at a point on the horizon line. The new idea is to use this common point on the horizon line to find the road border in the Hough domain. The input data for the Hough transformation is created by a set of local regularized edge detectors and an adaptive thresholding of the image. Since the image mostly shows low contrast, the edge extraction can hardly be realized by edge detectors with a small kernel. The image, therefore, is subsampled using the Gaussian pyramid technique and the preprocessing takes place in an optimal resolution level that is experimentally determined. The developed algorithm has been implemented on an experimental vehicle equipped with an infrared camera and was successfully tested in different situations.
{"title":"Hough transformation based approach for road border detection in infrared images","authors":"B. Fardi, G. Wanielik","doi":"10.1109/IVS.2004.1336443","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336443","url":null,"abstract":"This paper describes a real-time image processing algorithm for road border detection in infrared images. The basic idea is to couple the road border lines through the parallelism between them in the vehicle coordinate system. The parallelism of the two lines is translated in their convergence in the image plane due to the perspective projection. In this plane the two lines meet at a point on the horizon line. The new idea is to use this common point on the horizon line to find the road border in the Hough domain. The input data for the Hough transformation is created by a set of local regularized edge detectors and an adaptive thresholding of the image. Since the image mostly shows low contrast, the edge extraction can hardly be realized by edge detectors with a small kernel. The image, therefore, is subsampled using the Gaussian pyramid technique and the preprocessing takes place in an optimal resolution level that is experimentally determined. The developed algorithm has been implemented on an experimental vehicle equipped with an infrared camera and was successfully tested in different situations.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116026728","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 : 2004-06-14DOI: 10.1109/IVS.2004.1336490
A. Solé, O. Mano, G. Stein, H. Kumon, Y. Tamatsu, A. Shashua
In the context of combining radar and vision sensors for a fusion application in dense city traffic situations, one of the major challenges is to be able to validate radar targets. We take a high-level fusion approach assuming that both sensor modalities have the capacity to independently locate and identify targets of interest. In this context, radar targets can either correspond to a vision target- in which case the target is validated without further processing- or not. It is the latter case that drives the focus of this paper. A non-matched radar target can correspond to some solid object which is not part of the objects of interest of the vision sensor (such as a guard-rail) or can be caused by reflections in which case it is a ghost target which does not match any physical object in the real world. We describe a number of computational steps for the decision making of non-matched radar targets. The computations combine both direct motion parallax measurements and indirect motion analysis- which are not sufficient for computing parallax but are nevertheless quite effective- and pattern classification steps for covering situations which motion analysis are weak or ineffective. One of the major advantages of our high-level fusion approach is that it allows the use of simpler (low cost) radar technology to create a combined high performance system.
{"title":"Solid or not solid: vision for radar target validation","authors":"A. Solé, O. Mano, G. Stein, H. Kumon, Y. Tamatsu, A. Shashua","doi":"10.1109/IVS.2004.1336490","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336490","url":null,"abstract":"In the context of combining radar and vision sensors for a fusion application in dense city traffic situations, one of the major challenges is to be able to validate radar targets. We take a high-level fusion approach assuming that both sensor modalities have the capacity to independently locate and identify targets of interest. In this context, radar targets can either correspond to a vision target- in which case the target is validated without further processing- or not. It is the latter case that drives the focus of this paper. A non-matched radar target can correspond to some solid object which is not part of the objects of interest of the vision sensor (such as a guard-rail) or can be caused by reflections in which case it is a ghost target which does not match any physical object in the real world. We describe a number of computational steps for the decision making of non-matched radar targets. The computations combine both direct motion parallax measurements and indirect motion analysis- which are not sufficient for computing parallax but are nevertheless quite effective- and pattern classification steps for covering situations which motion analysis are weak or ineffective. One of the major advantages of our high-level fusion approach is that it allows the use of simpler (low cost) radar technology to create a combined high performance system.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128535968","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 : 2004-06-14DOI: 10.1109/IVS.2004.1336399
M.S. von Trzebiatowski, A. Gern, U. Franke, U.-P. Kaeppeler, P. Levi
This paper presents a new approach to the challenging task of lane recognition on general roads. Lane recognition is the basis for many driver assistance systems, including lane departure warning and the assignment of vehicles to specific lanes. Most systems of the past are designed for the well defined highway scenario. They rely on white lane markings with known geometric appearance. Our method is an extension which also works when lane markings are in bad conditions or missing completely. We use reflection posts as a means of estimating the course of the road. In addition we are furthermore able to measure the horizontal and vertical slope of the road surface.
{"title":"Detecting reflection posts - lane recognition on country roads","authors":"M.S. von Trzebiatowski, A. Gern, U. Franke, U.-P. Kaeppeler, P. Levi","doi":"10.1109/IVS.2004.1336399","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336399","url":null,"abstract":"This paper presents a new approach to the challenging task of lane recognition on general roads. Lane recognition is the basis for many driver assistance systems, including lane departure warning and the assignment of vehicles to specific lanes. Most systems of the past are designed for the well defined highway scenario. They rely on white lane markings with known geometric appearance. Our method is an extension which also works when lane markings are in bad conditions or missing completely. We use reflection posts as a means of estimating the course of the road. In addition we are furthermore able to measure the horizontal and vertical slope of the road surface.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"2008 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129039492","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 : 2004-06-14DOI: 10.1109/IVS.2004.1336411
H. Inoue, S. Osawa, A. Yashiki, H. Makino
The Japanese advanced cruise-assist highway system (AHS) provides driving support services through collaboration between the system and vehicle. AHS uses dedicated short-range communications (DSRC) for road-to-vehicle dialog that requires real-time and high-reliability operation. AHS-DSRC constitutes a small radio zone that provides driving support information in a cycle of 0.1 seconds. DSRC incorporates a marker beacon and an information beacon that are successively positioned at the roadside. This paper describes the AHS-DSRC was verified by experiment to provide a safety level of 99.1% or better.
{"title":"Dedicated short-range communications (DSRC) for AHS services","authors":"H. Inoue, S. Osawa, A. Yashiki, H. Makino","doi":"10.1109/IVS.2004.1336411","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336411","url":null,"abstract":"The Japanese advanced cruise-assist highway system (AHS) provides driving support services through collaboration between the system and vehicle. AHS uses dedicated short-range communications (DSRC) for road-to-vehicle dialog that requires real-time and high-reliability operation. AHS-DSRC constitutes a small radio zone that provides driving support information in a cycle of 0.1 seconds. DSRC incorporates a marker beacon and an information beacon that are successively positioned at the roadside. This paper describes the AHS-DSRC was verified by experiment to provide a safety level of 99.1% or better.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130515446","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 : 2004-06-14DOI: 10.1109/IVS.2004.1336463
A. Geistler, F. Bohringer
A robust odometer function providing a precise location information is a key element for modern on-board train location systems. In this paper, a robust and reliable velocity measurement with an eddy current sensor system is proposed. The sensor system is suitable especially for railway applications as no further installations are required on the track beyond the currently existing infrastructure. Two different methods of velocity measurement based on the eddy current sensor system are presented. As the system consists of two sensors in direction of movement, the most common way is a cross-correlation of the sensor signals to obtain the vehicle velocity. In addition, the shape of the sensor signals allows a frequency analysis, yielding an alternative measurement of the velocity. Fusing the velocity data in a Kalman filter provides an exact and precise location information of increased reliability.
{"title":"Robust velocity measurement for railway applications by fusing eddy current sensor signals","authors":"A. Geistler, F. Bohringer","doi":"10.1109/IVS.2004.1336463","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336463","url":null,"abstract":"A robust odometer function providing a precise location information is a key element for modern on-board train location systems. In this paper, a robust and reliable velocity measurement with an eddy current sensor system is proposed. The sensor system is suitable especially for railway applications as no further installations are required on the track beyond the currently existing infrastructure. Two different methods of velocity measurement based on the eddy current sensor system are presented. As the system consists of two sensors in direction of movement, the most common way is a cross-correlation of the sensor signals to obtain the vehicle velocity. In addition, the shape of the sensor signals allows a frequency analysis, yielding an alternative measurement of the velocity. Fusing the velocity data in a Kalman filter provides an exact and precise location information of increased reliability.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123810987","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 : 2004-06-14DOI: 10.1109/IVS.2004.1336452
P. J. Escamilla-Ambrosio, N. Lieven
The Autotaxi system is a safety critical sensor system that is being specially developed to perform the sensing required for an autonomous vehicle to drive safely along a dedicated paved guideway and to avoid collision. Therefore, the host vehicle is equipped with a set of sensors used to detect and track any object of interest in the field of view. In this work a multiple-sensor multiple-target tracking (MS-MTT) approach for the Autotaxi system is proposed. A decentralized MS-MTT system is considered for this application. It consists of two basic components: sensor-level tracking and multiple-sensor track fuser or fusion centre. Each sensor in the sensor-level is considered as an intelligent sensor which generates it own track file. Thus, the task of the fusion centre is to combine or fuse the local track files to produce a more accurate and reliable single system track file. This is performed in three stages: data alignment, track-to-track association, and track fusion.
{"title":"A multiple-sensor multiple-target tracking approach for the autotaxi system","authors":"P. J. Escamilla-Ambrosio, N. Lieven","doi":"10.1109/IVS.2004.1336452","DOIUrl":"https://doi.org/10.1109/IVS.2004.1336452","url":null,"abstract":"The Autotaxi system is a safety critical sensor system that is being specially developed to perform the sensing required for an autonomous vehicle to drive safely along a dedicated paved guideway and to avoid collision. Therefore, the host vehicle is equipped with a set of sensors used to detect and track any object of interest in the field of view. In this work a multiple-sensor multiple-target tracking (MS-MTT) approach for the Autotaxi system is proposed. A decentralized MS-MTT system is considered for this application. It consists of two basic components: sensor-level tracking and multiple-sensor track fuser or fusion centre. Each sensor in the sensor-level is considered as an intelligent sensor which generates it own track file. Thus, the task of the fusion centre is to combine or fuse the local track files to produce a more accurate and reliable single system track file. This is performed in three stages: data alignment, track-to-track association, and track fusion.","PeriodicalId":296386,"journal":{"name":"IEEE Intelligent Vehicles Symposium, 2004","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114829742","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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