基于改进ViBe的多行人检测方法

利用改进的Vi Be算法及模板匹配方法对多行人场景进行了目标检测.为了提高运动目标检测性能,提出将原Vi Be算法与帧间差分相结合的方法,该方法使二值图像中的鬼影比原Vi Be算法消除更为迅速.根据待处理像素点周围已完成的前背景分离结果,利用动态计算模型参数估计前背景,以提高前景目标提取的准确度.基于HOG算法识别运动目标中的行人目标.实验结果表明,该方法在没有降低运动物体检测实时性的同时,明显提高了算法检测的准确度.

Multi-pedestrian Detection Approach Based on Improved ViBe Algorithm

The moving object detection of multi-pedestrian scenario was conducted by using the improved ViBe algorithm and the template matching method. The original ViBe algorithm was combined with the frame difference method to improve the performance of moving object detection， which can more rapidly eliminate the ghosts in the result binary image than the original ViBe algorithm. According to the treated foreground result around the treating pixel， the dynamic model parameters were used to estimate the foreground for improving the accuracy of the foreground object detection. The HOG algorithm was used to detect the pedestrians in the moving objects. The results showed that the method does not reduce the real-time performance of moving object detection， and significantly improve the accuracy of the detection algorithm.