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多果蝇跟踪系统与航向。

Multiple Drosophila Tracking System with Heading Direction.

机构信息

Graduate School of Information Sciences, Tohoku University, Aramaki Aza Aoba 6-6-01, Aoba-Ku, Sendai 980-8579, Japan.

Graduate School of Engineering, Tohoku University, Aramaki Aza Aoba 6-6-01, Aoba-Ku, Sendai 980-8579, Japan.

出版信息

Sensors (Basel). 2017 Jan 5;17(1):96. doi: 10.3390/s17010096.

Abstract

Machine vision systems have been widely used for image analysis, especially that which is beyond human ability. In biology, studies of behavior help scientists to understand the relationship between sensory stimuli and animal responses. This typically requires the analysis and quantification of animal locomotion. In our work, we focus on the analysis of the locomotion of the fruit fly D r o s o p h i l a m e l a n o g a s t e r , a widely used model organism in biological research. Our system consists of two components: fly detection and tracking. Our system provides the ability to extract a group of flies as the objects of concern and furthermore determines the heading direction of each fly. As each fly moves, the system states are refined with a Kalman filter to obtain the optimal estimation. For the tracking step, combining information such as position and heading direction with assignment algorithms gives a successful tracking result. The use of heading direction increases the system efficiency when dealing with identity loss and flies swapping situations. The system can also operate with a variety of videos with different light intensities.

摘要

机器视觉系统已被广泛应用于图像分析,尤其是人类能力之外的图像分析。在生物学中,行为研究帮助科学家了解感官刺激与动物反应之间的关系。这通常需要分析和量化动物的运动。在我们的工作中,我们专注于分析果蝇 D r o s o p h i l a m e l a n o g a s t e r 的运动,果蝇是生物学研究中广泛使用的模式生物。我们的系统由两个组件组成:苍蝇检测和跟踪。我们的系统提供了提取一组苍蝇作为关注对象的能力,并进一步确定每只苍蝇的飞行方向。当每只苍蝇移动时,系统状态会通过卡尔曼滤波器进行细化,以获得最佳估计。在跟踪步骤中,将位置和飞行方向等信息与分配算法结合使用,可以得到成功的跟踪结果。在处理身份丢失和苍蝇交换的情况时,使用飞行方向可以提高系统的效率。该系统还可以在不同光照强度的各种视频上运行。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e7/5298669/50966a57f48d/sensors-17-00096-g001.jpg

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