Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Semi-supervised statistical region refinement for color image segmentation
Pattern Recognition
Semi-automatic video object segmentation using seeded region merging and bidirectional projection
Pattern Recognition Letters
Interactive point-and-click segmentation for object removal in digital images
ICCV'05 Proceedings of the 2005 international conference on Computer Vision in Human-Computer Interaction
Object tracking for retrieval applications in MPEG-2
IEEE Transactions on Circuits and Systems for Video Technology
Automatic segmentation of moving objects in video sequences: a region labeling approach
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the H.264/AVC video coding standard
IEEE Transactions on Circuits and Systems for Video Technology
Video object segmentation: a compressed domain approach
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Automatic moving object extraction for content-based applications
IEEE Transactions on Circuits and Systems for Video Technology
Global motion estimation from coarsely sampled motion vector field and the applications
IEEE Transactions on Circuits and Systems for Video Technology
Real-time moving object segmentation in H.264 compressed domain based on approximate reasoning
International Journal of Approximate Reasoning
Estimating motion reliability to improve moving object detection in the H.264/AVC domain
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Interactive inquiry for object of interest in video playback by motion-augmented graph cut
Proceedings of the international conference on Multimedia
Moving object segmentation in the h.264 compressed domain
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Motion compensated compressed domain watermarking
Proceedings of the 21st ACM international conference on Multimedia
Spatiotemporal saliency detection and salient region determination for H.264 videos
Journal of Visual Communication and Image Representation
Hi-index | 0.00 |
This paper presents a real-time spatiotemporal segmentation approach to extract video objects in the H.264 compressed domain. The only exploited segmentation cue is the motion vector (MV) field extracted from the H.264 compressed video. MV field is first temporally and spatially normalized and then accumulated by an iteratively backward projection scheme to enhance the salient motion. Then global motion compensation is performed on the accumulated MV field, which is also moderately segmented into different motion-homogenous regions by a modified statistical region growing algorithm. The hypothesis testing using the block residuals of global motion compensation is employed for intra-frame classification of segmented regions, and the projection is exploited for inter-frame tracking of previous video objects. Using the above results of intra-frame classification and inter-frame tracking as input, a correspondence matrix based spatiotemporal segmentation approach is proposed to segment video objects under different situations including appearing and disappearing objects, splitting and merging objects, stopping moving objects, multiple object tracking and scene change in a unified and efficient way. Experimental results for several H.264 compressed video sequences demonstrate the real-time performance and good segmentation quality of the proposed approach.