Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan, Republic of China.
PLoS One. 2012;7(4):e34784. doi: 10.1371/journal.pone.0034784. Epub 2012 Apr 4.
In recent years, there have been extensive studies aimed at decoding the DNA. Identifying the genetic cause of specific changes in a simple organism like Drosophila may help scientists recognize how multiple gene interactions may make some people more susceptible to heart disease or cancer. Investigators have devised experiments to observe changes in the gene networks in mutant Drosophila that responds differently to light, or have lower or higher locomotor activity. However, these studies focused on the behavior of the individual fly or on pair-wise interactions in the study of aggression or courtship. The behavior of these activities has been captured on film and inspected by a well-trained researcher after repeatedly watching the recorded film. Some studies also focused on ways to reduce the inspection time and increase the accuracy of the behavior experiment.
In this study, the behavior of drosophila during courtship was analyzed automatically by machine vision. We investigated the position and behavior discrimination during courtship using the captured images. Identification of the characteristics of drosophila, including sex, size, heading direction, and wing angles, can be computed using image analysis techniques that employ the Gaussian mixture model. The behavior of multiple drosophilae can also be analyzed simultaneously using the motion-prediction model and the variation constraint of heading direction.
The overlapped fruit flies can be identified based on the relationship between body centers. Moreover, the behaviors and profiles can be correctly recognized by image processing based on the constraints of the wing angle and the size of the body. Therefore, the behavior of the male fruit flies can be discriminated when two or three fruit flies form a close cluster. In this study, the courtship behavior, including wing songs and attempts, can currently be distinguished with accuracies of 95.8% and 90%, respectively.
近年来,人们进行了广泛的研究,旨在对 DNA 进行解码。鉴定像果蝇这样的简单生物中特定变化的遗传原因,可以帮助科学家了解多个基因相互作用如何使某些人更容易患心脏病或癌症。研究人员设计了实验来观察对光反应不同、或运动活性更低或更高的突变果蝇中的基因网络变化。然而,这些研究集中在个体果蝇的行为上,或者在研究攻击或求偶时集中在两两相互作用上。这些活动的行为已经被拍摄下来,并在经过反复观看记录的影片后,由训练有素的研究人员进行检查。一些研究还集中在如何减少检查时间和提高行为实验的准确性上。
在这项研究中,果蝇在求偶期间的行为是通过机器视觉自动分析的。我们使用捕获的图像来研究求偶期间的位置和行为差异。可以使用图像分析技术,包括高斯混合模型,来计算果蝇的特征,包括性别、大小、头部方向和翅膀角度的识别。使用运动预测模型和头部方向的变化约束,也可以同时分析多个果蝇的行为。
基于身体中心之间的关系,可以识别重叠的果蝇。此外,通过基于翅膀角度和身体大小的约束的图像处理,可以正确识别行为和轮廓。因此,当两到三只果蝇形成紧密的集群时,可以区分雄果蝇的行为。在这项研究中,翅膀歌曲和求偶尝试等求偶行为目前可以分别以 95.8%和 90%的准确度来区分。