Real-time automated concurrent visual tracking of many animals and subsequent behavioural compilation

J. Zelek, D. Bullock
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引用次数: 2

Abstract

One of our major research focus areas is real-time visual tracking and monitoring of moving and static objects in a video sequence. In particular we are interested in (1) object localization (also referred to as the focus of attention) which involves identifying the object of interest, (2) tracking the object using a model of the object which was initiated in step 1, and (3) understanding the accumulation of movements of the object over time (i.e., behavior). The objects of interiest for the purpose of this proposal are pigs. Automatically monitoring pigs via a non-invasively placed camera in their pens is interesting because the pigs are monitored in their natural habitat. Visual tracking involves modelling the object of interest and keeping track of its position and orientation through time. Issues include tracker recovery from error and preventing the tracker from jumping to other pigs. we have been able to demonstrate tracking pigs at about 10-15 Hz, however, the tracker tends to drift off the target eventually. We have only experimented with a single pig but our initial tests indicate that we can probably track at least 10 pigs simultaneously. Some unknowns include determining how quickly the pigs move and the type of motions, including quick jerky movements. Our preliminary investigations revealed that a blob tracker is insufficient for producing accurate traces.
许多动物的实时自动并发视觉跟踪和随后的行为汇编
我们的主要研究重点之一是视频序列中运动和静态物体的实时视觉跟踪和监控。我们特别感兴趣的是(1)对象定位(也称为注意力焦点),它涉及识别感兴趣的对象,(2)使用在步骤1中启动的对象模型跟踪对象,以及(3)理解对象随时间的运动积累(即行为)。这个提议的目标是猪。通过在猪圈中放置非侵入性摄像头来自动监控猪很有趣,因为猪是在它们的自然栖息地被监控的。视觉跟踪包括对感兴趣的对象建模,并随着时间的推移跟踪其位置和方向。问题包括跟踪器从错误中恢复,防止跟踪器跳到其他猪身上。我们已经能够以10-15赫兹的频率跟踪猪,然而,跟踪器最终会偏离目标。我们只对一头猪进行了实验,但初步测试表明,我们可能可以同时追踪至少10头猪。一些未知因素包括确定猪的移动速度和运动类型,包括快速的突然运动。我们的初步调查表明,斑点跟踪器不足以产生准确的痕迹。
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