Segmentation and tracking of video objects: suited to content-based video indexing, interactive television and production systems

Abstract

This paper examines the problem of segmentation and tracking of video objects for a content-based information retrieval context. Our method starts first with an interactive video object selection, then alternately tracks and fits the object of interest as long as possible. A user-based selection is required in order to initialize the process, whereas an active contour model progressively refines the selection by fitting the natural edges of the object. The video object is thus tracked by using a hybrid structure combining a hierarchical mesh for the motion estimation between two frames and a multi-resolution active contour model. This contour model is derived directly from the mesh boundaries in order to reposition the snake's nodes onto the natural edges of the object.