A Method for Detecting Road Spills Under the Constraint of Short Term-Long Term Dual Background Model

With the development of urban traffic and the occurrence of a large number of traffic accidents, the use of video-based traffic event detection instead of human real-time monitoring of traffic scenes, automatic detection and identification of road obstacles such as spills that may cause traffic accidents has become a hot spot in the research of intelligent transportation systems. This paper addresses the problem of low accuracy of existing video surveillance spills detection, proposes a short term-long term dual background model constrained road spills detection method and applies it to the detection of road spills traffic events, combines the classification recognition results of classifier to eliminate misjudgment and realize the event detection of road spills, and also realizes the 3D information recovery of spills and extracts 3D height information to complete the spills target recognition. It has good application value for constructing a perfect highway event detection, management and diversion system. At the same time, the research of this paper also lays a good foundation for the subsequent work of traffic event detection, computer vision reconstruction, etc. It has important guiding significance and reference value.