Name
Abstract | ||
|---|---|---|
Camera motion estimation plays an important role in digital video analysis algorithms such as video indexing and retrieval or automatic movie analysis. Several algorithms have been proposed to solve this problem in MPEG videos. This paper presents an optical flow-based approach for the camera motion estimation in all kinds of digital video formats, especially in movies. It compares the motion vector fields (MVFs) with six predefined templates to determine the type of motion. The MVFs are generated by using high-accuracy optical flow computation. The advantage of the method lies in its robustness to noisy environments such as false motion vectors and object motions. Comprehensive experiments with video clips extracted from well-known feature movies demonstrate the performance of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1504/IJISTA.2010.036578 | IJISTA |
Keywords | Field | DocType |
video clip,automatic movie analysis,digital video analysis,digital video format,false motion vector,robust method,video indexing,mpeg video,motion vector field,camera motion estimation,optical flow,object motion,films,movies | Computer vision,Block-matching algorithm,Quarter-pixel motion,Motion detection,Motion compensation,Image processing,Artificial intelligence,Motion estimation,Engineering,Optical flow,Motion vector | Journal |
Volume | Issue | Citations |
9 | 3/4 | 4 |
PageRank | References | Authors |
0.49 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nhat-Tan Nguyen | 1 | 11 | 1.35 |
| Denis Laurendeau | 2 | 803 | 169.72 |
| Alexandra Branzan-Albu | 3 | 11 | 1.35 |