SIFT has been proven to be the most robust local invariant feature descriptor. SIFT is designed mainly for gray images. However, color provides valuable information in object desc...
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Abstract. Most existing feature-point matching algorithms rely on photometric region descriptors to distinct and match feature points in two images. In this paper, we propose an eï...
Ping Li, Dirk Farin, Rene Klein Gunnewiek, Peter H...
We evaluate the performance of MPEG-7 image signatures, Compressed Histogram of Gradients descriptor (CHoG) and Scale Invariant Feature Transform (SIFT) descriptors for mobile vis...
Vijay Chandrasekhar, David M. Chen, Andy Lin, Gabr...
Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...