Detection of Independent Motion Using Directional Motion Estimation

It is shown that the problem of independent motion detection can be addressed by analyzing constraints on low-dimensional directional (projected) components of flow fields. We construct a robust algorithm, implemented as a recursive filter, to extract directional motion parameters from long image sequences. Based on this, a qualitative approach is described to detect independent motion, involving a combination of robust line-fitting and one-dimensional search. The low-dimensional projections onto subspaces facilitate efficient dynamic self-adaptation of detection thresholds to achieve good performance under changing operational conditions. The analysis is extended to long image sequences by incorporating tracking and spatio-temporal filtering. The approach is applicable to general camera motion and cluttered scenes using a wide range of camera fields of view. We demonstrate it on a variety of real image sequences.