【摘要】 立体视觉的核心问题是通过立体匹配算法获得准确的视差值,然而大多数现有的立体匹配算法无法在低纹理或接近无纹理的区域中获得准确的视差值。为了解决低纹理区域匹配精度相对偏低、高精度半全局匹配算法运算量较大的问题,文中提出了一种基于自适应滑动窗口的立体匹配算法。首先通过AD-Census变换计算匹配代价,然后针对不同区域调节聚合窗口形状及像素点权重,最后结合符合人体视觉特征的多尺度代价聚合框架获得聚合匹配代价,采用赢者通吃策略获取最终的稠密视差图。实验结果证明,该算法在低纹理区域的误匹配率相比较传统方案的下降范围为5.8%～21.68%,运算时间较半全局算法更短。更多还原

【Abstract】 The key problem of stereo vision is to obtain accurate disparity values through stereo matching algorithms.However,most existing stereo matching algorithms are unable to obtain accurate and correct disparities in low-texture regions.In this paper,in order to solve the problems of low matching accuracy of low texture regions and large computational complexity of high-precision semi-global matching algorithm,a stereo matching algorithm based on adaptive sliding window was proposed.The cost volume is calculated by AD-Census transform firstly.The shape of the aggregate window and the weight of the pixels are adjusted for different regions.The cross-scale cost aggregation framework conforming to the human visual feature is used to obtain the aggregate cost volume.Finally,the "winner take all strategy" is used to obtain the final disparity maps.Experiments show that the mismatch rate of the algorithm in low-texture regions decrease form 5.8% to 21.68%,which is lower than that of the traditional scheme,and the computation time is shorter than the semi-global algorithm.更多还原