An automatic system for recognizing fly courtship patterns via an image processing method.

IF 4.7 2区 心理学 Q1 BEHAVIORAL SCIENCES Behavioral and Brain Functions Pub Date : 2024-03-16 DOI:10.1186/s12993-024-00231-4
Ching-Hsin Chen, Yu-Chiao Lin, Sheng-Hao Wang, Tsung-Han Kuo, Hung-Yin Tsai
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Abstract

Fruit fly courtship behaviors composed of a series of actions have always been an important model for behavioral research. While most related studies have focused only on total courtship behaviors, specific courtship elements have often been underestimated. Identifying these courtship element details is extremely labor intensive and would largely benefit from an automatic recognition system. To address this issue, in this study, we established a vision-based fly courtship behavior recognition system. The system based on the proposed image processing methods can precisely distinguish body parts such as the head, thorax, and abdomen and automatically recognize specific courtship elements, including orientation, singing, attempted copulation, copulation and tapping, which was not detectable in previous studies. This system, which has high identity tracking accuracy (99.99%) and high behavioral element recognition rates (> 97.35%), can ensure correct identification even when flies completely overlap. Using this newly developed system, we investigated the total courtship time, and proportion, and transition of courtship elements in flies across different ages and found that male flies adjusted their courtship strategy in response to their physical condition. We also identified differences in courtship patterns between males with and without successful copulation. Our study therefore demonstrated how image processing methods can be applied to automatically recognize complex animal behaviors. The newly developed system will largely help us investigate the details of fly courtship in future research.

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通过图像处理方法识别苍蝇求偶模式的自动系统。
由一系列动作组成的果蝇求偶行为一直是行为学研究的重要模型。虽然大多数相关研究都只关注求偶行为的整体,但具体的求偶要素往往被低估。识别这些求偶要素的细节极其耗费精力,而自动识别系统则能在很大程度上解决这一问题。为了解决这个问题,我们在本研究中建立了一个基于视觉的苍蝇求偶行为识别系统。该系统基于所提出的图像处理方法,可精确区分头部、胸部和腹部等身体部位,并自动识别特定的求偶要素,包括定向、歌唱、尝试交配、交配和拍打等,而这些在以往的研究中是无法检测到的。该系统具有较高的身份跟踪准确率(99.99%)和较高的行为要素识别率(> 97.35%),即使在苍蝇完全重叠的情况下也能确保正确识别。利用这一新开发的系统,我们研究了不同年龄段苍蝇的求偶总时间、比例以及求偶要素的转换,发现雄蝇会根据身体状况调整其求偶策略。我们还发现了交配成功和未交配成功的雄蝇在求偶模式上的差异。因此,我们的研究展示了如何应用图像处理方法来自动识别复杂的动物行为。新开发的系统将在很大程度上帮助我们在未来的研究中探究苍蝇求偶的细节。
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来源期刊
Behavioral and Brain Functions
Behavioral and Brain Functions 医学-行为科学
CiteScore
5.90
自引率
0.00%
发文量
11
审稿时长
6-12 weeks
期刊介绍: A well-established journal in the field of behavioral and cognitive neuroscience, Behavioral and Brain Functions welcomes manuscripts which provide insight into the neurobiological mechanisms underlying behavior and brain function, or dysfunction. The journal gives priority to manuscripts that combine both neurobiology and behavior in a non-clinical manner.
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