Motion-Based Foreground Image Segmentation

Abstract

A variety of useful applications demonstrate the need for precise motion-based segmentation of image data. Video compression techniques rely heavily on accurate and efficient representation of spatio- temporal regions possessing similar motion models. In addition a variety of cinematographic effects are potentially possible with successful separation of a moving object's image from an arbitrary background. Computer vision systems often depend on the ability to distinguish or describe a moving object in an image sequence. This paper proposes a methodology, which separates a moving foreground from a stationary background in a general video sequence. It replaces or removes moving persons or objects in motion pictures. The problem is motivated primarily by the need for replacing or removing moving persons or objects in motion pictures. The main complication exists in this problem is the issue of occlusions with the background. Consider a speaker that moves their hand behind a stationary background object such as a desk or chair. Such occlusions represent a challenge and are not examined in this approach. In addition to ignoring occlusions, the following analysis makes other assumptions about a given image sequence. Lighting and color changes should not be present to a high degree in the video being examined. Furthermore, the moving object should be constrained towards the interior of the image.