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引用次数: 120

摘要

在特定环境中跟踪时,物体往往会在特定位置出现和消失。这些位置可能对应于门、车库、隧道入口,甚至是摄像机视图的边缘。具有这些位置知识的跟踪系统能够改进跟踪序列的初始化、破碎跟踪序列的重构和跟踪序列终止的确定。此外,这些位置的知识对于跟踪序列的活动级描述和理解非重叠相机视图之间的关系是有用的。本文介绍了一种同时解决这些耦合问题的方法:对一个场景的源汇模型进行参数推断;修复损坏的跟踪序列和其他跟踪故障。还解释了一种模型选择标准,它允许确定环境中源和汇的数量。在多种环境下的结果验证了该方法的有效性。
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Estimating Tracking Sources and Sinks
When tracking in a particular environment, objects tend to appear and disappear at certain locations. These locations may correspond to doors, garages, tunnel entrances, or even the edge of a camera view. A tracking system with knowledge of these locations is capable of improved initialization of tracking sequences, reconstitution of broken tracking sequences, and determination of tracking sequence termination. Further, knowledge of these locations is useful for activity-level descriptions of tracking sequences and for understanding relationships between non-overlapping camera views. This paper introduces a method for simultaneously solving these coupled problems: inferring the parameters of a source and sink model for a scene; and fixing broken tracking sequences and other tracking failures. A model selection criterion is also explained which allows determination of the number of sources and sinks in an environment. Results in multiple environments illustrate the effectiveness of this method.
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