Generalized Image Acquisition and Analysis

An evaluation of optical flow algorithms for background oriented schlieren imaging

The background oriented schlieren method (BOS) allows for accurate flow measurements with a simple experimental configuration. To estimate per-pixel displacement vectors between two images, BOS systems traditionally borrow window-based algorithms from particle image velocimetry. In this paper, we evaluate the performance of more recent optical flow methods in BOS settings. We also analyze the impact of different background patterns, suggesting the use of a pattern with detail at many scales. Experiments with both synthetic and real datasets show that the performance of BOS systems can be significantly improved through a combination of optical flow algorithms and multiscale background.

Projects

Interactive Geometry-Aware Segmentation for the Decomposition of Kaleidoscopic Images

Oliver Klehm, Ilya Reshetouski, Elmar Eisemann, Hans-Peter Seidel, Ivo Ihrke
VMV 2012



Abstract

Mirror systems have recently emerged as an alternative low-cost multi-view imaging solution. The use of these systems critically depends on the ability to compute the background of a multiply mirrored object. The images taken in such systems show a fractured, patterned view, making edge-guided segmentation difficult. Further, global illumination and light attenuation due to the mirrors make standard segmentation techniques fail. We therefore propose a system that allows a user to do the segmentation manually. We provide convenient tools that enable an interactive segmentation of kaleidoscopic images containing three-dimensional objects. Hereby, we explore suitable interaction and visualization schemes to guide the user. To achieve interactivity, we employ the GPU in all stages of the application, such as 2D/3D rendering as well as segmentation.
Video Demo Data Set

Bibtex

@InProceedings{Klehm12,
author = {Oliver Klehm, Ilya Reshetouski, Elmar Eisemann, Hans-Peter Seidel, and Ivo Ihrke},
title = "{Interactive Geometry-Aware Segmentation for the Decomposition of Kaleidoscopic Images }",
booktitle = {Proceedings of VMV},
pages = "xx--yy",
year = {2012},
}
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