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

BlurTags: Spatially Varying PSF Estimation with Out-of-Focus Patterns

Alexander Reuter, Hans-Peter Seidel, Ivo Ihrke
In: WSCG Communication Papers, 2012



Abstract

In this paper, we consider the problem of animation reconstruction, i.e., the reconstruction of shape and motion of a deformable object from dynamic 3D scanner data, without using user provided template models. Unlike pre- vious work that addressed this problem, we do not rely on locally conver- gent optimization but present a system that can handle fast motion, tem- porally disrupted input, and can correctly match objects that disappear for extended time periods in acquisition holes due to occlusion. Our approach is motivated by cartography: We first estimate a few landmark correspon- dences, which are extended to a dense matching and then used to recon- struct geometry and motion. We propose a number of algorithmic building blocks: a scheme for tracking landmarks in temporally coherent and inco- herent data, an algorithm for robust estimation of dense correspondences under topological noise, and the integration of local matching techniques to refine the result. We describe and evaluate the individual components and propose a complete animation reconstruction pipeline based on these ideas. We evaluate our method on a number of standard benchmark data sets and show that we can obtain correct reconstructions in situations where other techniques fail completely or require additional user guidance such as a template model.

Bibtex

@InProceedings{Reuter12,
author = {Alexander Reuter and Hans-Peter Seidel and Ivo Ihrke},
title = {BlurTags: spatially varying PSF estimation with out-of-focus patterns},
booktitle = {Proceedings of WSCG (Communication Papers)},
year = 2012,
pages = "xx--yy",
}
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