Automatic Director of Live Sport Based on Motion State

This paper introduces automatic director method of live sport based on motion state. The method is to combine the video frames of multi-channel cameras and use larger and more complete panoramic video for video content analysis and semantic event detection. Then, through the state analysis of the sport, it is determined whether the match at that moment is in Play or Break state. If the match is in Play state, it is adopted to place the motion target in the center of the guide screen. If the game is in the Break state, the sliding window method is adopted to build a HCRF model to mine the potential feature relationship between multimodal semantic clues and semantic events, so as to realize the detection of specific semantic events in sports videos, and to smoothly track the guide screen for extraction. We have done experiments on football match videos, and the results show that our method can generate coherent edited videos in line with audience psychology and achieve good visual effects, which also lays a foundation for the application of artificial intelligence to the automatic director of sports events.