
doi: 10.1007/11552499_68
In this paper, we propose an algorithm to characterize camera motion in video sequences based on image feature analysis. The approach predicts camera motion using spatio-temporal information obtained from tracking selected feature points throughout an image sequence. The spatio-temporal information provides the advantage of rich visual characteristic along a larger temporal scale over the traditional approaches, which tend to formulate computational methodologies on a few adjacent frames. The algorithm detects five basic camera motions of stationary, panning, tilting, zooming, and the combination of panning and tilting. We conduct the experiments to verify the proposed approach using real compressed video sequences. The experimental results have demonstrated the performance of proposed approach in determining camera motion.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
