Fast and Efficient Local Features Detection for Building Recognition

The vast growth of image databases creates many challenges for computer vision applications, for instance image retrieval and object recognition. Large variation in imaging conditions such as illumination and geometrical properties (including scale, rotation, and viewpoint) gives rise to the need for invariant features; i.e. image features should have minimal differences under these conditions. Local image features in the form of key points are widely used because of their invariant properties. In this chapter, we analyze different issues relating to existing local feature detectors. Based on this analysis, we present a new approach for detecting and filtering local features. The proposed approach is tested in a real-life application which supports navigation in urban environments based on visual information. The study shows that our approach performs as well as existing methods but with a significantly lower number of features.