This paper describes a novel multi-view matching framework based on a new type of invariant feature. Our features are located at Harris corners in discrete scale-space and oriente...
Matthew Brown, Richard Szeliski, Simon A. J. Winde...
In this paper, the matching of SIFT-like features [5] between images is studied. The goal is to decide which matches between descriptors of two datasets should be selected. This m...
Traditional benchmarking methods for information retrieval (IR) are based on experimental performance evaluation. Although the metrics precision and recall can measure the perform...
Dawei Song, Kam-Fai Wong, Peter Bruza, Chun Hung C...
—This paper presents a novel probabilistic approach to hierarchical, exemplar-based shape matching. No feature correspondence is needed among exemplars, just a suitable pairwise ...
This paper studies a framework for matching an unknown
number of corresponding structures in two images
(shapes), motivated by detecting objects in cluttered background
and lear...