Kalman filtering motion prediction for recursive spatio-temporal segmentation and object tracking
F. Ziliani, F. Moscheni · 1997
. In the framework of computer vision, the spatio-temporal segmentation procedure plays a central role. It aims at identifying in the input image, semantically meaningful features that are relevant for the problem at hand. In this paper, these features are selected to be the objects forming the scene. The objects are defined by their properties of temporal and spatial coherence through the video sequence. They provide a complete partition of the scene into its constituent components. Furthermore, the characteristics of the objects permit to track them through time. In this paper, a technique based on a discrete Kalman filter algorithm is proposed to follow the trajectory of the objects. The aim is to obtain a precise prediction of their position and motion. The accurate prediction improves both the recursive spatio-temporal segmentation and object tracking performances, enabling a high level understanding of the scene dynamics. The derived scene representation obtained finds applicati...