Digital video processing
Applications of Video-Content Analysis and Retrieval
IEEE MultiMedia
Moving object segmentation by background subtraction and temporal analysis
Image and Vision Computing
An efficient two-pass MAP-MRF algorithm for motion estimation based on mean field theory
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Automatic Segmentation of Non-rigid Objects in Image Sequences Using Spatiotemporal Information
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
New optical flow approach for motion segmentation based on gamma distribution
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
| Hi-index | 0.00 |
In this paper, we propose a new motion segmentation algorithm for accurate moving object segmentation. The proposed algorithm is elaborately designed based on Markov random field (MRF) model. When motion decision is performed on each pixel in images by detection theory, false decisions such as miss and false alarm are occurred. These false decisions cause segmentation errors of moving objects. We remove these errors by using MRF model based on Bayes rule. By means of experiments on test sequences, we demonstrate that our algorithm achieves good performance with respect to the segmentation accuracy.