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2009 IEEE Intelligent Vehicles Symposium最新文献

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Incorporating contextual information in pedestrian recognition 结合上下文信息的行人识别
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164305
Magdalena Szczot, O. Lohlein, Matthias Serfling, G. Palm
{"title":"Incorporating contextual information in pedestrian recognition","authors":"Magdalena Szczot, O. Lohlein, Matthias Serfling, G. Palm","doi":"10.1109/IVS.2009.5164305","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164305","url":null,"abstract":"Local classifiers are often used in automotive pedestrian detection systems. The disadvantage of such systems is that they only regard local image cutouts to discriminate pedestrian class from its background. In those cases where false alarms bear a great resemblance to true positives it is difficult to solve the classification task in that way. As a possible solution this paper presents a general and mathematically founded model which incorporates the pedestrian contextual information in the classification task. Our approach allows the use of any relevant contextual information to improve the detection results. This contribution shows how to define possible contextual hints and how to combine them into a contextual classifier.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"2018 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114215557","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}
引用次数: 4
A robust video based traffic light detection algorithm for intelligent vehicles 一种基于视频的鲁棒智能交通信号灯检测算法
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164332
Yehu Shen, U. Ozguner, K. Redmill, Jilin Liu
{"title":"A robust video based traffic light detection algorithm for intelligent vehicles","authors":"Yehu Shen, U. Ozguner, K. Redmill, Jilin Liu","doi":"10.1109/IVS.2009.5164332","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164332","url":null,"abstract":"Recently, researches on intelligent vehicles which can drive in urban environment autonomously become more popular. Traffic lights are common in cities and are important cues for the path planning of intelligent vehicles. In this paper, a robust and efficient algorithm to detect traffic lights based on video sequences captured by a low cost off-the-shelf video camera is proposed. The algorithm models the hue and saturation according to Gaussian distributions and learns their parameters with training images. From learned models, candidate regions of the traffic lights in the test images can be extracted. Post processing method which takes account of the shape information is applied to the candidate regions. Furthermore, detection results of the previous image frames are aggregated in order to provide a more robust result. Experimental results on several video sequences captured in typical urban environment prove the effectiveness of the proposed algorithm.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114848635","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}
引用次数: 80
Pavement image enhancement based on scale evaluation using nonsubsampled contourlet coefficients 基于非下采样contourlet系数尺度评价的路面图像增强
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164286
Li He, Shiru Qu, Daqi Zhang
{"title":"Pavement image enhancement based on scale evaluation using nonsubsampled contourlet coefficients","authors":"Li He, Shiru Qu, Daqi Zhang","doi":"10.1109/IVS.2009.5164286","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164286","url":null,"abstract":"This paper describes a scale evaluation method using nonsubsampled contourlet transform and its application in pavement image enhancement for crack detection. Crack in some scales is much more visible than in others, so a method for scale evaluation is given, and different gains are delivered to each scale for enhancement after scale evaluation. In the first step, noise threshold is computed by noise estimation. And then, sub-groups with 64×64 pixels are divided from the full image at each scale, and group direction variances of these sub-groups are computed for scale evaluation. At last, enhancing process at different scales are taken with gains obtained from scale evaluation. Experiment results show a promising use of the presented method for pavement image enhancement.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124138477","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}
引用次数: 0
Tracking stationary extended objects for road mapping using radar measurements 用雷达测量跟踪道路测绘用的固定扩展物体
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164312
C. Lundquist, U. Orguner, T. Schon
{"title":"Tracking stationary extended objects for road mapping using radar measurements","authors":"C. Lundquist, U. Orguner, T. Schon","doi":"10.1109/IVS.2009.5164312","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164312","url":null,"abstract":"It is getting more common that premium cars are equipped with a forward looking radar and a forward looking camera. The data is often used to estimate the road geometry, tracking leading vehicles, etc. However, there is valuable information present in the radar concerning stationary objects, that is typically not used. The present work shows how stationary objects, such as guard rails, can be modeled and tracked as extended objects using radar measurements. The problem is cast within a standard sensor fusion framework utilizing the Kalman filter. The approach has been evaluated on real data from highways and rural roads in Sweden.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127887934","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}
引用次数: 33
Detection and recognition of traffic signs in adverse conditions 在不利条件下检测和识别交通标志
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164300
Weijie Liu, K. Maruya
{"title":"Detection and recognition of traffic signs in adverse conditions","authors":"Weijie Liu, K. Maruya","doi":"10.1109/IVS.2009.5164300","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164300","url":null,"abstract":"Many techniques have been developed for traffic sign recognition, but it seems related systems have hardly been applied in real vehicles. One reason is that a visible-light camera can not give competent performance in adverse conditions. In the paper, we discuss how to make the best use of a visible-light camera for over-exposure and under-exposure conditions. Two approaches are developed to enhance our traffic sign recognition system. One concerns adaptive procedures for image processing. When candidates of traffic signs are detected, their transformation to binary images and matching with templates is implemented adaptively according to their brightness distributions. Another concerns auto exposure control of an on-vehicle camera. Results of the detection component and the recognition component are accumulated temporally for several video frames, and a weighted average of them is used to pick up important regions of the current frame for traffic sign recognition. Then exposure control is performed to ensure the selected regions be reasonably bright. Initial experiment results have shown obvious improvement.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125446181","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}
引用次数: 14
Probability estimation for an automotive Pre-Crash application with short filter settling times 具有短滤波器沉淀时间的汽车碰撞前应用的概率估计
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164313
M. Muntzinger, Sebastian Zuther, K. Dietmayer
{"title":"Probability estimation for an automotive Pre-Crash application with short filter settling times","authors":"M. Muntzinger, Sebastian Zuther, K. Dietmayer","doi":"10.1109/IVS.2009.5164313","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164313","url":null,"abstract":"In this paper, the merits of incorporating covariance propagation into a real-time Pre-Crash application are investigated. The suggested Pre-Crash algorithm activates restraint systems, such as a reversible seat belt tightening system, before an unavoidable accident happens. Sensor fusion of two short-range and one long-range radar with a target-based fusion is used to realize this vehicle safety application. A powerful, yet applicable method for using not only state but also covariance information for triggering actuators is proposed. A comprehensive parameter study on simulated as well as on real data shows statistically significant improvements in detection rate. Further, the importance of covariance errors in terms of accuracy for Pre-Crash applications is demonstrated. Even with few detection cycles and short filter settling times, a good compromise between detection rate and false alarms can be deduced.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127987881","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}
引用次数: 20
A robust autonomous freeway driving algorithm 鲁棒高速公路自动驾驶算法
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164420
Junqing Wei, J. Dolan
{"title":"A robust autonomous freeway driving algorithm","authors":"Junqing Wei, J. Dolan","doi":"10.1109/IVS.2009.5164420","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164420","url":null,"abstract":"This paper introduces a robust prediction- and cost-function based algorithm for autonomous freeway driving. A prediction engine is built so that the autonomous vehicle is able to estimate human drivers' intentions. A cost function library is used to help behavior planners generate the best strategies. Finally, the algorithm is tested in a real-time vehicle simulation platform used by the Tartan Racing Team for the DARPA Urban Challenge 2007.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131970046","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}
引用次数: 31
NVH research Based on Fuel Cell Vehicle 基于燃料电池汽车的NVH研究
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164473
Xiumin Shen, S. Zuo, Shiwei Zhang, Lin Li, L. He
{"title":"NVH research Based on Fuel Cell Vehicle","authors":"Xiumin Shen, S. Zuo, Shiwei Zhang, Lin Li, L. He","doi":"10.1109/IVS.2009.5164473","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164473","url":null,"abstract":"This paper presents the results of Noise Vibration and Harshness (NVH) study based on the Source-Transfer-Receiver Model in Fuel Cell Vehicle (FCV) [1]. Above all, vibro-acoustic testing of FCV was conducted, and through signal analyzing the main noise and vibration sources were identified to be the regenerative fan and air filter, component parts of the air auxiliary system. Then Transfer Path Analysis technique was applied to identify the main transfer paths from noise and vibration sources to the interior of the vehicle, to measure transfer functions linking source locations to target locations and to estimate the internal vibro-acoustic comfort in operating conditions. Finally feasible noise and vibration reduction measures were proposed based on the vibro-acoustic characteristics of the FCV discussed above.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131500958","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}
引用次数: 0
Unifying real-time multi-vehicle tracking and categorization 统一实时多车跟踪和分类
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164277
F. Bardet, T. Chateau, D. Ramadasan
{"title":"Unifying real-time multi-vehicle tracking and categorization","authors":"F. Bardet, T. Chateau, D. Ramadasan","doi":"10.1109/IVS.2009.5164277","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164277","url":null,"abstract":"This paper addresses real-time automatic visual tracking and classification of a variable number of vehicles in traffic. This off-board surveillance device may cooperate with on-board Advanced Driver Assistance Systems (ADAS), extending its measurement range to the areas of the road that are not in the car sensors field-of-view (in a curve or an intersection). Tracking results also are useful for statistical trajectory analysis, devoted to understanding and improving user-user and user-infrastructure interactions. As a main contribution, this paper proposes to unify vehicle tracking and classification in a single processing step. This paper also addresses a vehicle anisotropic distance measurement based on the vehicle 3D geometric model. Real time tracking results are shown and discussed on road sequences involving various types of vehicles such as motorcycles, cars, light trucks and heavy trucks.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125226748","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}
引用次数: 11
Non-linear, shape independent object tracking based on 2D lidar data 基于二维激光雷达数据的非线性、形状无关的目标跟踪
2009 IEEE Intelligent Vehicles Symposium Pub Date : 2009-06-03 DOI: 10.1109/IVS.2009.5164334
M. Thuy, F. Puente León
{"title":"Non-linear, shape independent object tracking based on 2D lidar data","authors":"M. Thuy, F. Puente León","doi":"10.1109/IVS.2009.5164334","DOIUrl":"https://doi.org/10.1109/IVS.2009.5164334","url":null,"abstract":"The paper presents a new lidar-based approach to object tracking. To this end, range data are recorded by two vehicle-born lidar scanners and registered in a common coordinate system. In contrary to common approaches, particle filters are employed to track the objects. This ensures no linearization of the underlying non-linear process model and, thus, a decreasing estimation error. For the object association, a new method is proposed that considers the knowledge about the object shape as well. Based on a statistical formulation, this ensures a robust object assignment even in ambiguous traffic scenes.","PeriodicalId":396749,"journal":{"name":"2009 IEEE Intelligent Vehicles Symposium","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132913659","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}
引用次数: 30
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