In this paper, we study texture metamorphosis, or how to generate texture samples that smoothly transform from a source texture image to a target. We propose a patternbased approach to specify the feature correspondence between two textures, based on the observation that many texture images have stochastically distributed patterns which are similar to each other. First, the user selects a patte...

The correspondence problem in computer vision is basically a matching task between two or more sets of features. In this paper, we introduce a vectorized image representation, which is a feature-based representation where correspondence has been established with respect to a reference image. The representation consists of two image measurements made at the feature points: shape and texture. Fea...

The paper presents an algorithm for deformable image registration based on point features extracted from input images using the Harris corner detector. The correspondence between the points extracted from the different images is established using RANdom SAmple Consensus (RANSAC) method with the affine and perspective global transformation used to model the deformations. The initial corresponden...

We present an object recognition system built on a combination of feature- and correspondence-based pattern recognizers. The feature-based part, called preselection network, is a single-layer feedforward network weighted with the amount of information contributed by each feature to the decision at hand. For processing arbitrary objects, we employ small, regular graphs whose nodes are attributed...

Finding point correspondences plays an important role in automatically building statistical shape models from a training set of 3D surfaces. For the point correspondence problem, Davies et al. [1] proposed a minimum-description-length-based objective function to balance the training errors and generalization ability. A recent evaluation study [2] that compares several well-known 3D point corres...

In this paper, we propose a new approach for establishing the correspondence between local invariant features using Bayesian graph matching algorithm. First, we will discuss various local invariant feature detectors and descriptors for scale and affine transformation and illumination changes. Second, we propose an efficient features corresponding method using local invariant features and new gr...