Intelligent Multi-objective Anomaly Detection Method Based on Robust Sparse Flow

• 作者: Ke Wang Ningjiang Chen Weishan Huang Yan Chen Ziqi He
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 工学
• 关键词: Traffic anomaly detection KLT algorithm Sparse optical flow Forward-Backward error
• 年，卷（期）: 2020,（2）
• 页码范围: 445-457
• 页数: 13页
• 分类号: TN9

摘要

To meet the needs of transportation systems for smart scenic security services,real-time detection and identification of traffic anomalies with high accuracy is essential.Based on the multi-objective sparse optical flow estimation method based on KLT algorithm,an improved algorithm for robust sparse optical flow is designed.The Forward-Backward error calculation method was used to eliminate the error optical flow generated by the KLT algorithm and the robustness of optical flow was improved.The proposed algorithm was verified by the actual traffic scene monitoring example,and the anomaly detection accuracy is above 80%.Furthermore,it has good detection effect on the benchmark dataset.