Abstract:
A traffic flow estimation mechanism is proposed for highway surveillance systems with scenes tampered by raindrops. To detect rain-drop tampered scenes, features are extr...Show MoreMetadata
Abstract:
A traffic flow estimation mechanism is proposed for highway surveillance systems with scenes tampered by raindrops. To detect rain-drop tampered scenes, features are extracted via salient region detection and block segmentation. Feature selection is performed to select more discriminative features. For traffic flow estimation, daytime and night time models are performed separately to adapt to the characteristics of the surveillance scenes. Finally, an effective graph-based mapping method is designed to map the vehicle count sequences to per minute traffic flow. The system is tested with a highly challenging dataset. The accuracy of the traffic flow analysis is satisfying with low mean absolute errors even when the cameras are seriously tampered by rain.
Published in: 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)
Date of Conference: 18-21 September 2019
Date Added to IEEE Xplore: 25 November 2019
ISBN Information: