A VOP generation tool: Automatic segmentation of moving objects in image sequences based on spatio-temporal information

Abstract

The new MPEG-4 video coding standard enables content-based functionalities. In order to support the philosophy of the MPEG-4 visual standard, each frame of video sequences should be represented in terms of video object planes (VOP's), In other wards, video objects to be encoded in still pictures or video sequences should be prepared before the encoding process starts. Therefore, it requires a prior decomposition of sequences into VOP's so that each VOP represents a moving object, This paper addresses an image segmentation method for separating moving objects from the background in image sequences, The proposed method utilizes the following spatio-temporal information, 1) For localization of moving objects in the image sequence, two consecutive image frames in the temporal direction are examined and a hypothesis testing is performed by comparing two variance estimates from two consecutive difference images, which results in an F-test. 2) Spatial segmentation is performed to divide each image into semantic regions and to find precise object boundaries of the moving objects. The temporal segmentation yields a change detection mask that indicates moving areas (foreground) and nonmoving areas (background), and spatial segmentation produces spatial segmentation masks. A combination of the spatial and temporal segmentation masks produces VOP's faithfully, This paper presents various experimental results.