In image retrieval, most existing approaches that incorporate local features produce high dimensional vectors, which lead to a high computational and data storage cost. Moreover, ...
—We propose a novel scenario called “writer retrieval” consisting in the retrieval from a set of documents all those produced by the same writer. The retrieval is based on a ...
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
In this paper, we investigate the mathematical problem underlying segmentation of hybrid motions: Given a series of tracked feature correspondences between two (perspective) image...
Exhibiting new features and likely related matching techniques to efficiently retrieve images from databases remains an open problem. This paper is first devoted to such a novel d...