多特征融合的Camshift算法及其进一步改进

基于颜色核的Camshift算法可以有效实现简单场景下的目标跟踪,但在光线变化明显或目标与背景颜色相近的场景下易受干扰。为此,采用颜色、边缘梯度、纹理等多个特征自适应融合的方式改进算法,提高算法应对光线变化的能力；并通过修正特征直方图、设置合理搜索范围对算法进行进一步改进,解决相似背景的干扰问题。实验结果显示,在光照变化明显或目标与背景特征相近的场景中,改进的算法与传统算法相比具有更高的跟踪精度。

Multi-feature fusion Camshift algorithm and its further improvement

The Camshift algorithm based on color-kernel can effectively track objects in a simple background,but it is easy to be interfered by illumination variation or the similar color object in the background.To improve the algorithm’s ability to respond to illumination variation,a multi-feature adaptive fusion scheme based on color,shape and texture was proposed.And further improvements have been proposed through modifying feature histogram and setting a reasonable search region to solve the problem of similar background.The experimental results show that the improved algorithm has higher tracking accuracy than traditional algorithm in the scene with illumination variation or similar background.