
In this paper, we discuss a number of new problems that arise in image databases, and that set them apart from traditional databases. The fact that image databases are based on similarity, rather than matching, creates a whose set of new issues.Most noticeably, while matching is, by and large, a well defined concept, there are many possible types of similarities. In this paper, we consider the problem of simulating human similarity perception. We argue that a satisfactory solution is possible for preattentive similarity, and we present a general and comprehensive geometric similarity model.
| citations 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). | 13 | |
| 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). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
