Occlusion/disocclusion detection using K-means clustering near object boundary with comparison of average motion of clusters to object and background motions
US7142600B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 21, 2003 |
| Grant date | Nov 28, 2006 |
| Priority date | — |
| Expiry date | Apr 30, 2025 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N19/61
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
An object in a video sequence is tracked by object masks generated for frames in the sequence. Macroblocks are motion compensated to predict the new object mask. Large differences between the next frame and the current frame detect suspect regions that may be obscured in the next frame. The motion vectors in the object are clustered using a K-means algorithm. The cluster centroid motion vectors are compared to an average motion vector of each suspect region. When the motion differences are small, the suspect region is considered part of the object and removed from the object mask as an occlusion. Large differences between the prior frame and the current frame detect suspected newly-uncovered regions. The average motion vector of each suspect region is compared to cluster centroid motion vectors. When the motion differences are small, the suspect region is added to the object mask as a disocclusion.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.