Name
Abstract | ||
|---|---|---|
A scene containing multiple independently moving, possibly occluding, rigid objects is considered under the weak perspective camera model. We obtain a set of feature points tracked across a number of frames and address the problem of 3D motion segmentation of the objects in presence of measurement noise and outliers. We extend the robust structure from motion (SfM) method [5] to 3D motion segmentation and apply it to realistic, contaminated tracking data with occlusion. A number of approaches to 3D motion segmentation have already been proposed [3, 6, 14, 15]. However, most of them were not developed for, and tested on, noisy and outlier-corrupted data that often occurs in practice. Due to the consistent use of robust techniques at all critical steps, our approach can cope with such data, as demonstrated in a number of tests with synthetic and real image sequences. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/978-3-540-70932-9_4 | WDV |
Keywords | Field | DocType |
feature point,outlier-corrupted data,critical step,robust structure,measurement noise,weak perspective,consistent use,contaminated tracking data,real image sequence,robust technique,motion segmentation,structure from motion | Structure from motion,Computer vision,Motion field,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Motion estimation,Match moving | Conference |
Volume | ISSN | ISBN |
4358 | 0302-9743 | 3-540-70931-2 |
Citations | PageRank | References |
3 | 0.42 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Levente Hajder | 1 | 43 | 12.55 |
| Chetverikov, D. | 2 | 956 | 99.89 |