Daphnia magna is a widely adopted biological indicator for studying the environmental toxicity in aquatic ecosystems. Due to the tiny size and appearance similarity of Daphnia most behavioral tracking systems can only record the behavioral movement of a single individual. In this work, a novel behavioral tracking scheme is proposed to track the group movement of Daphnia and record the accurate trajectory of each individual. Individual position, motion estimation and appearance similarity are incorporated to solve the multiple objects tracking problem. Optical flow is utilized to estimate individual motion and identify each individual in occlusions. Normalized cross correlation is employed to measure appearance similarity of Daphnia individuals. According to these feature movement trajectories are assigned to each individual by linear optimization. The main advantage of the proposed method is to segment individual Daphnia from occluded images according to the appearance and motion characters. Consequently, the success rate of tracking under occlusions could be significantly improved. The proposed method was tested on 8 video clips which captured in two different observation conditions. The correct identification ratio reached 94.74% and the average success ratio was 87.68%. The comparison tests proved that our method was superior to a well-known multiple object tracking method in dealing with occlusions. The proposed Daphnia tracking scheme was reliable and could provide accurate movement information for behavioral and environmental studies.

大型蚤（Daphnia magna）是研究水生生态系统环境毒性的一种广泛采用的生物指示剂。由于水蚤的大小和外观相似性，大多数行为跟踪系统只能记录单个人的行为运动。在这项工作中，提出了一种新颖的行为跟踪方案来跟踪水蚤的群体运动并记录每个人的准确轨迹。单独的位置，运动估计和外观相似性被合并以解决多目标跟踪问题。利用光流来估计个体运动并识别阻塞中的每个个体。归一化互相关用于测量水蚤的外观相似性个人。根据这些特征，通过线性优化将运动轨迹分配给每个个体。该方法的主要优点是根据外观和运动特征从被遮挡的图像中分割单个水蚤。因此，可以显着提高遮挡下跟踪的成功率。该方法在8个视频剪辑上进行了测试，这些视频剪辑在两种不同的观察条件下捕获。正确识别率达到94.74％，平均成功率为87.68％。对比测试证明，在遮挡方面，我们的方法优于众所周知的多对象跟踪方法。拟议的水蚤 跟踪方案是可靠的，可以为行为和环境研究提供准确的运动信息。