论文标题
微观视频中动态对象行为描述的折叠功能
Foldover Features for Dynamic Object Behavior Description in Microscopic Videos
论文作者
论文摘要
行为描述有助于分析微小对象，相似对象，具有弱视觉信息的对象以及具有相似视觉信息的对象，在微观视频中对动态对象的识别和分类中起着基本作用。为此，我们提出了折叠功能来描述动态对象的行为。首先，我们分别以X，Y和Z方向为微观视频中的每个对象生成折叠率。然后，我们分别使用统计方法从X，Y和Z方向提取折叠功能。最后，我们使用四个不同的分类器来测试提出的折叠功能的有效性。在实验中，我们使用精子显微镜视频数据集评估所提出的折叠功能，包括三种类型的1374个精子，并获得96.5％的最高分类精度。
Behavior description is conducive to the analysis of tiny objects, similar objects, objects with weak visual information and objects with similar visual information, playing a fundamental role in the identification and classification of dynamic objects in microscopic videos. To this end, we propose foldover features to describe the behavior of dynamic objects. First, we generate foldover for each object in microscopic videos in X, Y and Z directions, respectively. Then, we extract foldover features from the X, Y and Z directions with statistical methods, respectively. Finally, we use four different classifiers to test the effectiveness of the proposed foldover features. In the experiment, we use a sperm microscopic video dataset to evaluate the proposed foldover features, including three types of 1374 sperms, and obtain the highest classification accuracy of 96.5%.
