Real-Time Stereo Mosaicing Using Feature Tracking

Abstract

Real-time creation of video mosaics needs fast and accurate motion computation. While most mosaicing methods can use 2D image motion, the creation of multi view stereo mosaics needs more accurate 3D motion computation. Fast and accurate computation of 3D motion is challenging in the case of unstabilized cameras moving in 3D scenes, which is always the case when stereo mosaics are used. Efficient blending of the mosaic strip is also essential. Most cases of stereo mosaicing satisfy the assumption of limited camera motion, with no forward motion and no change in internal parameters. Under these assumptions uniform sideways motion creates straight epipolar lines. When the 3D motion is computed correctly, images can be aligned in space-time volume to give straight epipolar lines, a method which is depth invariant. We propose to align the video sequence in a space-time volume based on efficient feature tracking, and in this paper we used Kernel Tracking. Computation is fast as the motion in computed only for a few regions of the image, yet giving accurate 3D motion. This computation is faster and more accurate than the previously used direct approach. We also present "Barcode Blending", a new approach for using pyramid blending in video mosaics, which is very efficient. Barcode Blending overcomes the complexity of building pyramids for multiple narrow strips, combining all strips in a single blending step. The entire stereo mosaicing process is highly efficient in computation and in memory, and can be performed on mobile devices.