A cooperative Top-Down/Bottom-Up Technique for Motion Field Segmentation

The segmentation of video sequences into regions underlying a coherent motion is one of the most useful processing for video analysis and coding. In this paper, we propose an algorithm that exploits the advantages of both top-down and bottom-up techniques for motion eld segmentation. To remove camera motion, a global motion estimation and compensation is rst performed. Local motion estimation is then carried out relying on a traslational motion model. Starting from this motion eld, a two-stage analysis based on ane models takes place. In the rst stage, using a top-down segmentation technique, macro-regions with coherent ane motion are extracted. In the second stage, the segmentation of each macro-region is rened using a bottom-up approach based on a motion vector clustering. In order to further improve the accuracy of the spatio-temporal segmentation, a Markov Random Field (MRF)-inspired motion-and-intensity based renement step is performed to adjust objects boundaries

Coding-Oriented Video Segmentation Inspired by MRF Models

This paper presents an approach to the segmentation of video sequences that is inspired by Markov random field (MRF) models and is aimed at region-based video compression. Two goals of the segmentation algorithm are considered: to assure a rate-efficient partitioning of video sequences and to provide regions that are meaningful for human observers ("coding for content"). To address both issues we extend our earlier work; we incorporate a segmentation complexity measure to account for the rate allocated to region shape, we use a robust error criterion to reject outliers in the intensity residual and we incorporate a temporal consistency constraint to assure the continuity of segmentation in time. We demonstrate improvements in the segmentation for real videoconferencing sequences. 1. INTRODUCTION Current trend towards region-based video coding derives from the inadequate quality provided by traditional blockbased schemes at very low bit rates. Advanced coding schemes based on arbitrar..