Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The origina...
Image matching is a fundamental task of many problems in computer vision. This paper presents a novel local feature descriptor based on the gradient distance and orientation histo...
SIFT descriptor has been widely applied in computer vision and object recognition, but has not been explored in the field of handwritten Chinese character recognition. In this pap...
We propose in this paper a face authentication method based on a similarity measure. The SIFT descriptor is used to define some interest keypoints characterized by an invariant pa...
Recognizing and localizing objects is a classical problem in computer vision that is an important stage for many automated systems. In order to perform object recognition many res...
This paper introduces an affine invariant shape descriptor for maximally stable extremal regions (MSER). Affine invariant feature descriptors are normally computed by sampling the...
Matching points between multiple images of a scene is a vital component of many computer vision tasks. Point matching involves creating a succinct and discriminative descriptor fo...