Image registration finds a variety of applications in computer vision. Unfortunately, traditional image registration techniques tend to be costly. We present a new image registration technique that makes use of the spatial intensity gradient of the images to find a good match using a type of Newton-Raphson iteration. Our technique is faster because it examines far fewer potential matches between the images than existing techniques. Furthermore, this registration technique can be generalized to handle rotation, scaling and shearing. We show show our technique can be adapted for use in a stereo vision system. 1. Introduction Image registration finds a variety of applications in computer vision, such as image matching for stereo vision, pattern recognition, and motion analysis. Untortunately, existing techniques for image registration tend to be costly. Moreover, they generally fail to deal with rotation or other distortions of the images. In this paper we present a new image registratio...

This paper describes a method to extend the registration range of a vision-based augmented reality (AR) system. We propose to use natural feature points contained in images captured by a pair of stereo cameras in conjunction with pre-defined fixed fiducial markers. The system also incorporates an inertial sensor to achieve a robust registration method which can handle user's fast head rotation and movement. The system first uses pre-defined fiducial markers to estimate a projection matrix between real and virtual coordinate systems. At the same time, the system picks up and tracks a set of natural feature points from the initial image. As a user moves around in an AR environment, the initial markers fall out from the camera frame and natural features are then used to recover the projection matrix. Experiments for evaluating the feasibility of the method are carried out and show the potential benefits of the method.

Image registration finds a variety of applications in computer vision. Unfortunately, traditional image registration techniques tend to be costly. We present a new image registration technique that makes use of the spatial intensity gradient of the images to find a good match using a type of Newton-Raphson iteration. Our technique is faster because it examines far fewer potential matches between the images than existing techniques. Furthermore, this registration technique can be generalized to handle rotation, scaling and shearing. We show show our technique can be adapted for use in a stereo vision system. 1. Introduction Image registration finds a variety of applications in computer vision, such as image matching for stereo vision, pattern recognition, and motion analysis. Untortunately, existing techniques for image registration tend to be costly. Moreover, they generally fail to deal with rotation or other distortions of the images. In this paper we present a new image registra...