
Feature detection and matching are an essential component of many computer vision applications. Consider the two pairs of images shown in Figure 4.2. For the first pair, we may wish to align the two images so that they can be seamlessly stitched into a composite mosaic (Chapter 9). For the second pair, we may wish to establish a dense set of correspondences so that a 3D model can be constructed or an in-between view can be generated (Chapter 11). In either case, what kinds of features should you detect and then match in order to establish such an alignment or set of correspondences? Think about this for a few moments before reading on.
| 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). | 7 | |
| 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. | Top 10% | |
| 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 |
