Time-resolved 3d capture of non-stationary gas flows

Atcheson, Bradley; Ihrke, Ivo; Heidrich, Wolfgang; Tevs, Art; Bradley, Derek; Magnor, Marcus; Seidel, Hans‐Peter

doi:10.1145/1457515.1409085

Cited by 41 publications

(38 citation statements)

References 39 publications

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“…The initial stage of our approach is most similar to a technique called Background Oriented Schlieren (BOS, a.k.a Synthetic Schlieren) [6,8,10,12,15,18]. The optical setup in Schlieren photography is replaced by optical flow calculations on a video of a fluid in front of an in-focus textured background.…”

Section: Related Workmentioning

confidence: 99%

“…1(c,d). Atcheson et al use BOS tomography to recover the volumetric 3D shape of air flow [6]. However, their technique requires a camera array that covers 180 • of the air flow of the interest, making the whole system difficult to use outdoors.…”

Section: Related Workmentioning

confidence: 99%

“…While artificial backgrounds are often used when performing BOS [6], Hargather et al [12] showed that natural backgrounds, such as a forest, are sufficiently textured for BOS, allowing for the visualization of large-scale air flows around planes and boats. To address the fact that the background must be in focus, Wetzstein et al [28] introduced light field BOS imaging in which the textured background is replaced by a light field probe.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Refraction Wiggles for Measuring Fluid Depth and Velocity from Video

Xue¹,

Rubinstein

Wadhwa³

et al. 2014

Computer Vision – ECCV 2014

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Abstract. We present principled algorithms for measuring the velocity and 3D location of refractive fluids, such as hot air or gas, from natural videos with textured backgrounds. Our main observation is that intensity variations related to movements of refractive fluid elements, as observed by one or more video cameras, are consistent over small space-time volumes. We call these intensity variations "refraction wiggles", and use them as features for tracking and stereo fusion to recover the fluid motion and depth from video sequences. We give algorithms for 1) measuring the (2D, projected) motion of refractive fluids in monocular videos, and 2) recovering the 3D position of points on the fluid from stereo cameras. Unlike pixel intensities, wiggles can be extremely subtle and cannot be known with the same level of confidence for all pixels, depending on factors such as background texture and physical properties of the fluid. We thus carefully model uncertainty in our algorithms for robust estimation of fluid motion and depth. We show results on controlled sequences, synthetic simulations, and natural videos. Different from previous approaches for measuring refractive flow, our methods operate directly on videos captured with ordinary cameras, do not require auxiliary sensors, light sources or designed backgrounds, and can correctly detect the motion and location of refractive fluids even when they are invisible to the naked eye.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Refraction Wiggles for Measuring Fluid Depth and Velocity from Video

Xue¹,

Rubinstein

Wadhwa³

et al. 2014

Computer Vision – ECCV 2014

View full text Add to dashboard Cite

show abstract

“…For specular correspondences with small spatial support, it is possible to derive algorithms that require significantly fewer images by employing learning approaches (Wexler et al, 2002) or even single images by optical flow (Atcheson et al, 2008). Peers and Dutré (2003) proposed the use of wavelets as illumination patterns for environment matting.…”

Section: Related Workmentioning

confidence: 99%

Non-Parametric Acquisition of Near-Dirac Pixel Correspondences

Atcheson

Heidrich

2012

Proceedings of the International Conference on Computer Vision Theory and Applications

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Abstract:Many computer vision and graphics applications require the acquisition of correspondences between the pixels of a 2D illumination pattern and those of captured 2D photographs. Trivial cases with only one-to-one correspondences require only a few measurements. In more general scenes containing complex inter-reflections, capturing the full reflection field requires more extensive sampling and complex processing schemes. We present a method that addresses the middle-ground: scenes where each pixel maps to a small, compact set of pixels that cannot easily be modeled parametrically. The coding method is based on optically-constructed Bloom filters and frequency coding. It is non-adaptive, allowing fast acquisition, robust to measurement noise, and can be decoded with only moderate computational power. It requires fewer measurements and scales up to higher resolutions more efficiently than previous methods.

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“…In reverse engineering, the noncontact coordinate measuring approaches based on laser triangulation measurement principle use multiple views of cameras to get the depth information of the object [1][2][3]. The object to be tested can be measured rapidly and precisely without any damage.…”

Section: Introductionmentioning

confidence: 99%

Shape Detection for Impeller Blades by Non-contact Coordinate Measuring Machine

Luo

2011

Computer and Computing Technologies in Agriculture IV

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Abstract. The impeller blades are very important and precise parts in turbine, but they can be worn and deformed easily. In this paper, we present a novel approach to detect the shape of the impeller blades. The proposed approach is to compare the designed 3D model of the impeller blades with the virtual 3D model of the tested part which is reconstructed by non-contact coordinate measuring machine. The non-contact coordinate measuring machine measures an object with optical triangulation, and then we can reconstruct a virtual 3D model for the part. In contrast to previous approaches which detect the parts with complex surface, the proposed shape detection approach is scatheless and reliable. Experimental results also show that our approach gets the shape of the tested part precisely and describes the deformed condition clearly.

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Time-resolved 3d capture of non-stationary gas flows

Cited by 41 publications

References 39 publications

Refraction Wiggles for Measuring Fluid Depth and Velocity from Video

Refraction Wiggles for Measuring Fluid Depth and Velocity from Video

Non-Parametric Acquisition of Near-Dirac Pixel Correspondences

Shape Detection for Impeller Blades by Non-contact Coordinate Measuring Machine

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