Edge computing enabled video segmentation for real-time traffic monitoring in internet of vehicles

Highlights：

• By analysing the motion magnitude of the videos, the proposed spatiotemporal interest points algorithm could eliminate a lot of superuous vehicle video at the edge.

• The video segmentation algorithm based on the multi-modal linear features combination divides the video sequence into segments of interests, and then extracts the video clips from these segments.

• An optimized YOLOv3 vehicle detection algorithm is presented based on edge computing, which greatly improves the detection speed and further meets the low latency and high accuracy requirements.

• The extensive numerical experimental verification results show our methods may achieve better performance, compared with the existing algorithms for different stages of the redundancy elimination, video segmentation, key frame selection and vehicle detection.