Dependent Motion Segmentation in Moving Camera Videos: A Survey

Abstract

Motion segmentation plays a central role in a variety of computer vision and pattern recognition applications. In moving camera videos, the dynamic background caused by camera motion and the object motions caused by multiple moving objects are mixed and dependent with each other making the segmentation of camera motion and object motions quite difficult. This is the known dependent motion segmentation. Although motion segmentation in static scenes is a relative easy work, the dependent motion segmentation in dynamic scenes is very challenging due to the high mixture and dependence between camera motion and object motions. Recently, a large number of works have been developed for the task of dependent motion segmentation. However, their performances are still far behind human perceptions. In this paper, we studied, analyzed, and reviewed the most important and recent developed dependent motion segmentation techniques and proposed a classification strategy to categorize these techniques into different groups according to their characteristics and features. Furthermore, we also discussed the advantages and disadvantages of each kind of techniques and provided suggestions for further research directions.