Abstract:
In this paper, we propose a coarse-to-fine segmentation method for extracting moving regions from compressed video. First, motion vectors are clustered to provide a coars...Show MoreMetadata
Abstract:
In this paper, we propose a coarse-to-fine segmentation method for extracting moving regions from compressed video. First, motion vectors are clustered to provide a coarse segmentation of moving regions at block level. Second, boundaries between moving regions are identified, and finally, a fine segmentation is performed within boundary regions using edge and color information. Experimental results show that the proposed method can segment moving regions fairly accurately, with sensitivity of 85% or higher, and specificity of over 95%.
Date of Conference: 06-08 May 2009
Date Added to IEEE Xplore: 29 May 2009
ISBN Information:
ISSN Information:
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Segmented Regions ,
- Video Compression ,
- Segmentation Method ,
- Boundary Region ,
- Color Information ,
- Final Segmentation ,
- Edge Information ,
- Motion Vector ,
- Root Mean Square Error ,
- Visual Comparison ,
- Regional Growth ,
- Segmentation Results ,
- Edge Detection ,
- False Alarm Rate ,
- Bitrate ,
- Bitstream ,
- Motion Estimation ,
- Least Significant Bit ,
- Percentage Of Pixels ,
- Local Edge ,
- Local Color ,
- Table Tennis ,
- Group Of Pictures ,
- Spatial Segmentation
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Segmented Regions ,
- Video Compression ,
- Segmentation Method ,
- Boundary Region ,
- Color Information ,
- Final Segmentation ,
- Edge Information ,
- Motion Vector ,
- Root Mean Square Error ,
- Visual Comparison ,
- Regional Growth ,
- Segmentation Results ,
- Edge Detection ,
- False Alarm Rate ,
- Bitrate ,
- Bitstream ,
- Motion Estimation ,
- Least Significant Bit ,
- Percentage Of Pixels ,
- Local Edge ,
- Local Color ,
- Table Tennis ,
- Group Of Pictures ,
- Spatial Segmentation