ORB-SLAM2: Sub-pixel interpolation formula in binocular stereo matching

Its code implementation is: 

// Step 4. 亚像素插值, 使用最佳匹配点及其左右相邻点构成抛物线来得到最小sad的亚像素坐标
            // 使用3点拟合抛物线的方式，用极小值代替之前计算的最优是差值
            //    \                 / <- 由视差为14，15，16的相似度拟合的抛物线
            //      .             .(16)
            //         .14     .(15) <- int/uchar最佳视差值
            //              . 
            //           （14.5）<- 真实的视差值
            //   deltaR = 15.5 - 16 = -0.5
            // 公式参考opencv sgbm源码中的亚像素插值公式
            // 或论文<<On Building an Accurate Stereo Matching System on Graphics Hardware>> 公式7

            const float dist1 = vDists[L+bestincR-1];	
            const float dist2 = vDists[L+bestincR];
            const float dist3 = vDists[L+bestincR+1];
            const float deltaR = (dist1-dist3)/(2.0f*(dist1+dist3-2.0f*dist2));

The deltaR here is  , the specific formula is as follows:

subpixel ineterpolation sub-pixel interpolation (conic curve fitting parallax value)

 The derivation here is as follows:

 That is, const float deltaR = (dist1-dist3)/(2.0f*(dist1+dist3-2.0f*dist2)); deltaR in the above formula is when h is 1

Reference: [Algorithm] Concise Analysis of OpenCV-SGBM Algorithm and Source Code_JinSu_'s Blog-CSDN Blog