Fig. 2

Spatial point projection and matching. \(\mathrm {I}_1\) ,\(\mathrm {I}_2\) are two adjacent frames, P is a dynamic feature point, \(\mathrm {P}_{i1}\) represents the pixel coordinates of dynamic feature point P in frame \(\mathrm {I}_1\) , \(\mathrm {P}_{i2}\) represents the pixel coordinates of P in frame \(\mathrm {I}_2\) , \(\mathrm {Q}_{i1}\) represents the predicted value \(\mathrm {Q}_{i1}\) corresponding to \(\mathrm {P}_{i1}\) calculated by BA method, \(\mathrm {P}_{i2}\) and \(\mathrm {Q}_{i1}\) will produce a certain deviation d between them, and the deviation needs to be reduced by continuously optimizing the transformation matrix of BA method. After the P point moves to the P’ position, the corresponding matching pixel becomes \(\mathrm {P'}_{i2}\) in the \(\mathrm {I}_2\) frame, and the deviation between \(\mathrm {P'}_{i2}\) and \(\mathrm {Q}_{i1}\) becomes d’