
Previous research in motion analysis of image sequences has generally not considered the basic nature of higher orders of motion such as acceleration. In this work, we disambiguate different types of motion, and in particular focus on acceleration. First, we show acceleration can be computed in a principled manner by extending Horn and Schunck's algorithm for global optical flow estimation. We then demonstrate an approximation of the acceleration field using an alternative established optical flow technique, since most real motions violate the global smoothness assumption of Horn and Schunck. Furthermore, we decompose acceleration into radial and tangential components for greater depth of understanding of the motion. As a general motion descriptor, we show how acceleration provides the capability for differentiating different types of motion in video sequences
| 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). | 2 | |
| 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 |
