Name
Abstract | ||
|---|---|---|
The extraction of a parametric global motion from a motion field is a task with several applications in video processing. We present two probabilistic formulations of the problem and carry out optimization using the RAST algorithm, a geometric matching method novel to motion estimation in video. RAST uses an exhaustive and adaptive search of transformation space and thus gives - in contrast to local sampling optimization techniques used in the past - a globally optimal solution. Among other applications, our framework can thus be used as a source of ground truth for benchmarking motion estimation algorithms. Our main contributions are: first, the novel combination of a state-of-the-art MAP criterion for dominant motion estimation with a search procedure that guarantees global optimality. Second, experimental results that illustrate the superior performance of our approach on synthetic flow fields as well as real-world video streams. Third, a significant speedup of the search achieved by extending the model with an additional smoothness prior. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74936-3_21 | DAGM-Symposium |
Keywords | Field | DocType |
rast algorithm,optimal dominant motion estimation,motion field,real-world video stream,motion estimation,video processing,dominant motion estimation,transformation space,adaptive search,parametric global motion,benchmarking motion estimation algorithm,search procedure | Video processing,Mathematical optimization,Block-matching algorithm,Motion field,Quarter-pixel motion,Motion estimation,Probabilistic logic,Mathematics,Speedup,Motion vector | Conference |
Volume | ISSN | Citations |
4713 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 15 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrian Ulges | 1 | 328 | 26.61 |
| Christoph H. Lampert | 2 | 2718 | 125.52 |
| Daniel Keysers | 3 | 1737 | 140.59 |
| Thomas M. Breuel | 4 | 2362 | 219.10 |