Accurate moving object segmentation in unconstraint videos based on robust seed pixels selection

Automatic Moving Object Segmentation with Accurate Boundaries

This paper presents a layer-model based method to segment moving objects from image sequence with accurate boundaries. The segmentation framework involves three stages: Motion seed detection, Motion layer expansion and Motion boundary refinement. In the first stage, motion seeds, which determine the amount and initial position of motion layers, are detected by corner matching between consecutiv...

Wavelet-based Moving Object Segmentation

Robust moving video object segmentation in the MPEG compressed domain

In this paper, we proposed a robust moving video object segmentation algorithm using features in the MPEG compressed domain. We first cluster the motion vectors and produce a motion mask. Then, a difference mask at 8 x 8 block size is extracted from the DC image by background subtraction method. Finally, the motion mask and the difference mask are combined conditionally to generate the final ob...

Robust 2D Moving Object Segmentation and Tracking in Video Sequences

− Unsupervised motion segmentation and tracking in video sequences is a complex task, requiring robust estimation and flexible modeling. The paper presents an unsupervised method of moving object segmentation and tracking in video sequences captured by static cameras. Central to our work is the nonparametric density estimation and the mean shift algorithm for finding local maxima of the probabi...

Object Segmentation in Videos from Moving Camera with MRFs on Color and Motion Features

In this paper we address the problem of fast segmenting moving objects in video acquired by moving camera or more generally with a moving background. We present an approach based on a color segmentation followed by a region-merging on motion through Markov Random Fields (MRFs). The technique we propose is inspired to a work of Gelgon and Bouthemy [6], that has been modified to reduce computatio...