Name
Abstract | ||
|---|---|---|
Multiview image sequence processing has been the focus of considerable attention in recent literature. This paper presents an efficient technique for object-based rigid and non-rigid 3D motion estimation, applicable to problems occurring in multiview image sequence coding applications. More specifically, a neural network is formed for the estimation of the rigid 3D motion of each object in the scene, using initially estimated 2D motion vectors corresponding to each camera view. Non-linear error minimization techniques are adopted for neural network weight update. Furthermore, a novel technique is also proposed for the estimation of the local non-rigid deformations, based on the multiview camera geometry. Experimental results using both stereoscopic and trinocular camera setups illustrate and evaluate the proposed scheme. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1016/S0923-5965(02)00131-5 | Signal Processing: Image Communication |
Keywords | Field | DocType |
Motion estimation,Rigid/non-rigid,Multiview | Computer vision,Stereoscopy,Computer science,Image processing,Coding (social sciences),Minification,Artificial intelligence,Motion estimation,Artificial neural network,Image sequence processing,Image sequence | Journal |
Volume | Issue | ISSN |
18 | 3 | 0923-5965 |
Citations | PageRank | References |
5 | 0.69 | 23 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ploskas, N. | 1 | 10 | 1.22 |
| D. Simitopoulos | 2 | 11 | 1.61 |
| Dimitrios Tzovaras | 3 | 1377 | 205.82 |
| George A. Triantafyllidis | 4 | 15 | 3.72 |
| M.G. Strintzis | 5 | 43 | 4.44 |