Title :
Patch-duplets for object recognition and pose estimation
Author :
Johansson, Björn ; Moe, Anders
Author_Institution :
Dept. of EE, Linkoping Univ., Sweden
Abstract :
This paper describes a view-based method for object recognition and estimation of object pose from a single image. The method is based on feature vector matching and clustering. A set of interest points is detected and combined into pairs. A pair of patches, centered around each point in the pair, is extracted from a local orientation image. The patch orientation and size depends on the relative positions of the points, which make them invariant to translation, rotation, and locally invariant to scale. Each pair of patches constitutes a feature vector. The method is demonstrated on a number of real images and the patch-duplet feature is compared to the SIFT feature.
Keywords :
feature extraction; image matching; object recognition; feature vector clustering; feature vector matching; local image descriptors; object pose estimation; object recognition; patch orientation; patch-duplet feature; view-based method; Computer vision; Data mining; Gaussian processes; Histograms; Laboratories; Object recognition; Prototypes; Robot vision systems; Robustness; Object recognition; local image descriptors; object pose estimation;
Conference_Titel :
Computer and Robot Vision, 2005. Proceedings. The 2nd Canadian Conference on
Print_ISBN :
0-7695-2319-6
DOI :
10.1109/CRV.2005.58