Name
Abstract | ||
|---|---|---|
We present a depth video enhancement algorithm in order to provide high quality haptic interaction. As the telecommunication technology emerges rapidly, the depth image-based haptic interaction is becoming viable for broadcasting applications. Since a real depth map usually contains discrete and rugged noise, its haptic interaction produces the distorted force feedback. To resolve these problems, we propose a two-step refinement and adaptive sampling algorithm. In the first step, noise is removed by the median-filtering technique in 2D image space. Since not all pixels can be used to reconstruct the 3D mesh due to limited system resources, the filtered map is adaptively sampled based on the depth variation. Sampled 2D pixels, called feature points, are triangulated and projected onto 3D space. In the second refinement step, we apply the Gaussian smoothing technique to the reconstructed 3D surface. Finally, 3D surfaces are rendered to compute a smooth depth map from Z-buffer. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1093/ietisy/e89-d.1.37 | IEICE Transactions |
Keywords | Field | DocType |
depth video enhancement,real depth,high quality haptic interaction,adaptive sampling algorithm,depth video enhancement algorithm,smooth depth map,gaussian smoothing technique,3d reconstruction,depth variation,haptic interaction,filtered map,image space,depth video,data refinement,smooth surface reconstruction,depth map,median filter,surface reconstruction,force feedback | Noise reduction,Iterative reconstruction,Computer vision,Median filter,Computer science,Gaussian blur,Pixel,Artificial intelligence,Depth map,Haptic technology,3D reconstruction | Journal |
Volume | Issue | ISSN |
E89-D | 1 | 1745-1361 |
Citations | PageRank | References |
20 | 1.70 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seung-Man Kim | 1 | 32 | 4.27 |
| Jongeun Cha | 2 | 255 | 21.24 |
| Jeha Ryu | 3 | 405 | 54.48 |
| Kwan H. Lee | 4 | 148 | 29.48 |