Volume 4,Issue 7
基于时序一致性约束的视频异常报警优化方法
针对弱监督视频异常检测中分数波动引起的报警频繁切换和短时误报，提出一种时序一致性报警后处理方法。该方法在16帧片段尺度上依次进行指数移动平均、双阈值判定、短间隔合并和最短持续时间约束，并利用校准子集确定工作点。基于DSANet 公开预训练模型，在UCF-Crime和XD-Violence上进行5次重复分层留出实验。F1工作点下，两个数据集的每百视频纯误报事件数分别由59.14降至24.91和10.81降至5.97，报警切换次数分别下降41.1%和19.9%，帧级F1基本保持。该方法无需重新训练，平均处理时间不超过1.94 ms/视频，但事件召回率略有下降，报警延迟有所增加。
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