Visual Features—From Early Concepts to Modern Computer Vision

Abstract

Extracting, representing and comparing image content is one of the most important tasks in the fields of computer vision and pattern recognition. Distinctive image characteristics are often described by visual image features which serve as input for applications such as image registration, image retrieval, 3D reconstruction, navigation, object recognition and object tracking. The awareness for the need of adequately describing visual features emerged in the 1920s in the domain of visual perception, and fundamental concepts have been established to which almost every approach for feature extraction can be traced back. After the transfer of the basic ideas to the field of computer vision, much research has been carried out including the development of new concepts and methods for extracting such features, the improvement of existing ideas and numerous comparisons of different methods. In this chapter, a definition of visual features is derived, and different types are presented which address both the spatial and the spatio-temporal domain. This includes local image features, which are used in a variety of computer vision applications, and their evolution from early ideas to powerful feature extraction and matching methods.