视频序列对称差分法检测与预测人脸技术

Face detection and prediction technology based on video surveillance

根据视频监控图像在时间和空间上的连续性和相关性,利用视频图像对称差分,找到运动区域,再结合人脸肤色的聚类特征确定出人脸候选区域,改进了基于规则的人脸定位方法,利用人脸的几何特征,实现复杂视频图像中的多人脸检测。运用运动系数加上横向和纵向调节因子,对后续帧中的人脸加以预测。实验表明,该算法复杂度小,准确率较高,对姿态、表情、背景等变化情况下人脸的检测均具有较好的鲁棒性,预测跟踪效果好。

Based on the continuity and relativity in time and space of video surveillance sequences, similar face areas were found in motion areas using symmetrical frame differences of video sequences and the clustering of skin-color features. By improving the algorithm for face locating and using geometric facial features, multiple faces were detected in complex video sequences. The faces in video sequences were predicted via motion quotiety and horizontal and vertical adjustment factors. The experimental results show that this algorithm has lower complexity, higher veracity, and better robustness in face detection in situations with changing gestures, expressions and backgrounds. The prediction and tracking effects are satisfied.