The invention relates to a logistic regression-based queuing anomaly detection method and device. The device comprises a hard disk video recorder module and a format conversion module; the hard disk video recorder module is a device for storing monitoring videos; monitoring videos collected by a business hall are stored in the hard disk video recorder; when queuing detection is performed on different windows or counters in the business hall, the video information of corresponding windows or counters is required to be read from the hard disk video recorder; when the video information is read, user names and passwords are required to be provided; the format conversion module performs format conversion on the videos; the format of the videos stored in the hard disk video recorder is a YUV format; and since the queuing detection is realized based on opencv, the YUV format is required to be converted into a format which is recognizable for the opencv. The logistic regression-based queuing anomaly detection method and device of the invention are superior to traditional head recognition means and can assist in solving the problem of poor universality. According to the method and device of the invention, a large number of head samples are adopted to perform training; an obtained classifier is utilized to recognize heads; and therefore, recognition accuracy can be improved, and interference is little.