|
DSpace@nitr >
National Institue of Technology- Rourkela >
Conference Papers >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/804
|
| Title: | Detection of slow moving video objects using compound Markov random Field model |
| Authors: | Subudhi, B N
Nanda, P K |
| Keywords: | Markov processes
image segmentation
image sequences
object detection
video signal processing |
| Issue Date: | 2008 |
| Publisher: | IEEE |
| Citation: | IEEE Region 10 Annual International Conference, Proceedings/TENCON, |
| Abstract: | Often, moving object detection in a video sequence has been achieved a variant of temporal segmentation methods. For slow moving video objects, a temporal segmentation method fails to detect the objects. In this paper, we propose a Markov random Field (MRF) model based scheme to detect slow movements in a video sequence. The proposed scheme is a combination of a proposed spatio-temporal segmentation scheme and temporal segmentation method. A compound MRF model is used in spatiotemporal framework. In this framework, the a priori distribution is MRF and this takes care of spatial distribution of current frame, temporal frames and the Change Detection Masks (CDM) of the temporal frames. The spatio-temporal segmentation problem is formulated as a pixel labeling problem in Maximum a posteriori (MAP) framework. The MAP estimates are obtained using a hybrid algorithm. These estimated labels are used to obtain the Video Object Plane (VOP) and hence the detection of objects. The results are com... |
| Description: | Copyright for the paper belongs to IEEE |
| URI: | http://dx.doi.org/10.1109/TENCON.2008.4766385
http://hdl.handle.net/2080/804 |
| Appears in Collections: | Conference Papers
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| bnsubudhi-2008-tencon.pdf | | 488Kb | Adobe PDF | View/Open |
|
Show full item record
All items in DSpace are protected by copyright, with all rights reserved.
|
