{"title":"从图像轨迹确定多物体三维运动和结构的一般方法","authors":"T. Y. Tian, M. Shah","doi":"10.1109/MNRAO.1994.346247","DOIUrl":null,"url":null,"abstract":"Presents a general approach to determine the 3D motion and structure of multiple objects undergoing arbitrary motions. We segment the scene based on 3D motion parameters. First, the general motion model is fitted to each single trajectory. For this nonlinear fitting, initial estimates are obtained by a linear multiple-motion SFM (structure from motion) algorithm using the first two frames. Next, trajectories are clustered into groups corresponding to different moving objects. In our approach, discontinuous trajectories, resulting from occlusion, are also allowed. Finally, multiple trajectory fitting is applied to each trajectory group to improve the estimates further. Our simulation results show that the proposed method is robust.<<ETX>>","PeriodicalId":336218,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A general approach for determining 3D motion and structure of multiple objects from image trajectories\",\"authors\":\"T. Y. Tian, M. Shah\",\"doi\":\"10.1109/MNRAO.1994.346247\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Presents a general approach to determine the 3D motion and structure of multiple objects undergoing arbitrary motions. We segment the scene based on 3D motion parameters. First, the general motion model is fitted to each single trajectory. For this nonlinear fitting, initial estimates are obtained by a linear multiple-motion SFM (structure from motion) algorithm using the first two frames. Next, trajectories are clustered into groups corresponding to different moving objects. In our approach, discontinuous trajectories, resulting from occlusion, are also allowed. Finally, multiple trajectory fitting is applied to each trajectory group to improve the estimates further. Our simulation results show that the proposed method is robust.<<ETX>>\",\"PeriodicalId\":336218,\"journal\":{\"name\":\"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MNRAO.1994.346247\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MNRAO.1994.346247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
提出了一种确定任意运动的多物体的三维运动和结构的一般方法。我们根据3D运动参数对场景进行分割。首先,将一般运动模型拟合到每条单轨迹上。对于这种非线性拟合,通过使用前两帧的线性多运动SFM (structure from motion)算法获得初始估计。接下来,将轨迹聚类成不同运动对象对应的组。在我们的方法中,由遮挡引起的不连续轨迹也是允许的。最后,对每个轨迹组进行多次轨迹拟合,进一步提高估计精度。仿真结果表明,该方法具有较好的鲁棒性
A general approach for determining 3D motion and structure of multiple objects from image trajectories
Presents a general approach to determine the 3D motion and structure of multiple objects undergoing arbitrary motions. We segment the scene based on 3D motion parameters. First, the general motion model is fitted to each single trajectory. For this nonlinear fitting, initial estimates are obtained by a linear multiple-motion SFM (structure from motion) algorithm using the first two frames. Next, trajectories are clustered into groups corresponding to different moving objects. In our approach, discontinuous trajectories, resulting from occlusion, are also allowed. Finally, multiple trajectory fitting is applied to each trajectory group to improve the estimates further. Our simulation results show that the proposed method is robust.<>