On the tracking of featureless objects with occlusion

G. Gordon
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引用次数: 10

Abstract

The author discusses an extremely efficient low-level tracking algorithm using only centers of gravity and sizes of the objects. He uses the center of gravity as the main tracking mechanism and the size of the object to aid in solving occlusion problems. Thus the size of the objects is mainly used as an aid in deciding how and if the number of objects changes from one frame to another. The author reports on experiments using video images of tennis balls bouncing through the field of vision. The camera is fixed and the lighting conditions are controlled. The balls are easily extracted from the background by subtraction of the image from a registered image of the background under the same lighting conditions. It is concluded that the proposed techniques can be applied to both video and infrared images, and are especially useful when the objects lack significant 'features' for matching.<>
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基于遮挡的无特征目标跟踪
作者讨论了一种仅使用物体的重心和大小的极有效的低级跟踪算法。他使用重心作为主要的跟踪机制和物体的大小来帮助解决遮挡问题。因此,对象的大小主要用作决定对象的数量如何以及是否从一个帧变化到另一个帧的辅助。作者报告了利用网球在视野中弹跳的视频图像进行的实验。相机是固定的,照明条件是可控的。在相同照明条件下,通过从背景的配准图像中减去图像,可以很容易地从背景中提取球。结论是,所提出的技术可以应用于视频和红外图像,并且在物体缺乏重要“特征”进行匹配时特别有用。
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Motion estimation from points without correspondences from orthographic projections Object tracking with a moving camera Stereo/motion cues in pre-attentive vision processing-some experiments with random-dot stereographic image sequences Second-order motion perception: space/time separable mechanisms A parallel motion algorithm consistent with psychophysics and physiology
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