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Social insects interact extensively with their mates. To reveal the mechanism of their sociality, it is important to observe the behavior of each individual in a colony and to analyze their social contexts. Recently, digital video cameras have become less expensive despite increases in their performance, enabling researchers to record the behavior in various places easily. However, much labor and time is needed to analyze the social behavior manually from the video footage. In this study, we propose a new method to detect and track multiple bees moving on a flat surface. Our proposed method consists of three core processes: (i) detecting the bee candidate regions using a background subtraction method and binarization, (ii) identifying individuals by a combination of overlapping information in temporal changes of position and simple prediction of the candidate regions based on the bee's movement, and (iii) outputting the locations and trajectories of the identified bees. Our system succeeds in processing a video of sixteen bees moving freely on a flat arena for three minutes. More than 95% of the bees' central points were successfully extracted and their trajectories precisely traced.