Name
Abstract | ||
|---|---|---|
The classical Mean Shift can't change the scale of tracking window in real time while tracking target is changing in size. This paper adopts graph cuts theory to the problem of scale adaptation for Mean Shift tracking. According to the result of Mean Shift iteration in every frame, implementing graph cuts using skin color Gaussian mixture model(GMM) in a small area around it, and updating tracking window size through the largest skin lump among the result of graph cuts. Experimental results clearly demonstrate that the method can reflect the real scale change of tracking target, avoid the interference of other objects in background, and has good usability and robustness. Besides it enriches manipulation method of Human Computer Interaction by controlling entertainment games. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CAD/Graphics.2011.36 | CAD/Graphics |
Keywords | Field | DocType |
graph cuts theory,mean shift tracking,scale adaptation,tracking window size,largest skin lump,mean shift iteration,real scale change,classical mean shift,graph cut,image segmentation,gaussian mixture model,graph cuts,real time,graph theory,human computer interaction,gaussian processes,mean shift | Cut,Graph theory,Computer vision,Graph cuts in computer vision,Computer science,Robustness (computer science),Image segmentation,Artificial intelligence,Gaussian process,Mean-shift,Mixture model | Conference |
Citations | PageRank | References |
1 | 0.39 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ling Zhao | 1 | 428 | 18.49 |
| Guocheng An | 2 | 3 | 1.71 |
| Fengjun Zhang | 3 | 54 | 6.09 |
| Hongan Wang | 4 | 642 | 79.77 |
| Guozhong Dai | 5 | 323 | 39.93 |