Instantaneous 3D motion from image derivatives using the Least Trimmed Square regression
Pattern Recognition Letters
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In this paper, we describe a robust method for the extraction of the apparent 3-D camera velocity and 3-D scene structure information. Our method performs the extraction of the apparent 3-D camera velocity in a fully automated way without any knowledge about 3-D scene content information as used in current methods. This has the advantage that it can be used to fully automate the generation of natural-looking virtual/augmented environments, as well as in video-database browsing. First, we describe our method for the robust extraction of 3-D parameters. This method is a combination of the eight-point method in structure-from-motion with a statistical technique to automatically select feature points in the image, irrespective of 3-D content information. Second, we discuss two applications which use the results of the 3-D parameter extraction. The first application is the generation of sprite layers using 3-D camera velocity information to represent an eight-parameter perspective image-to-sprite mapping plus 3-D scene depth information for the sprite layering. The second application is the use of 3-D camera velocity for the indexing of large video databases according to a set of seven independent types of camera motion. In this application, we discuss a formal video description structure-the camera-motion descriptor-which was successfully included in the working draft of the MPEG-7 video standard