基于高斯金字塔与差分法的多目标检测和跟踪算法

Multiple Objects Detection and Tracking Based on Background Subtraction and Gaussian Pyramid

针对复杂背景下的多目标检测和跟踪问题,提出了将背景差分目标检测算法与高斯金字塔图像重采样相结合的运动目标检测算法.该算法采用高斯金字塔法对图像进行重采样,建立背景模型,使用背景差分法获得前景区域,并对前景区域进行阴影检测、去除,从而检测出完整目标.融入了高斯模型关于背景更新的算法,克服了由于背景突然改变而造成的误检测.在目标阈值的确定过程中,采用动态阈值确定法,以提高目标检测的正确性.同时将目标的颜色特征和运动矢量引入到多目标跟踪算法中,提高目标跟踪的准确性.实验结果表明,该算法对于场景中存在目标频繁出现、消失、交叉运动和遮挡等情形均有较好的检测与跟踪效果.

For the multi--target tracking problems with complex background, a method combing background subtraction with Guassian pyramid on objects detection is presented. The method detects the whole object with taking sample on the objects with Guassian pyramid, building background model, extracting foreground areas with background subtraction, and eliminating the shadow on the foreground. The detection that integrates Gauss model concerning background renewal of calculation, overcomes the error resulted from the sudden change of background. A dynamic threshold concept is proposed to enhance detection effect and thus increase the possibility of implementation. Color model and motion feature is leaded in the method, so the veracity and security is enhanced. The experi- ment results have showed that the proposed algorithm is robust to the problems of the appearance and disappearance of targets, the cross movement of targets and occlusiorL