ИСТИНА

We consider the problem of people counting in video surveillance. This is one of the most popular tasks in video analysis, because this data can be used for predictive analytics and improvement of customer services, traffic control, etc. Our method is based on the object tracking in video with low framerate. We use the algorithm from as a baseline and propose several modifications that improve the quality of people counting. One of the main modifications is to use a head detector instead of a body detector in the tracking pipeline. Head tracking is proved to be more robust and accurate as the heads are less susceptible to occlusions. To find the intersection of a person with a signal line, we either raise the signal lines to the level of the heads or perform a regression of bodies based on the available head detections. Our experimental evaluation has demonstrated that the modified algorithm surpasses original in both accuracy and computational efficiency, showing a lower counting error on a lower detection frequency.