An Introduction to 3D Computer Vision Techniques and Algorithms

Cyganek, Bogusław

doi:10.1002/9780470699720

Cited by 251 publications

(181 citation statements)

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“…Further we demonstrate that the Fisher z-transformation (Fisher, 1921) and its confidence interval (Volkmann, 2009) are proper indicators for the accuracy and confidence of a fit, which allow to identify over-interpreted regions of the map. Finally, we leverage all this information by using the concept of multi-scale image pyramids (Cyganek, 2009), well known in the field of image analysis, to significantly reduce the required computational resources and time to perform a fit by up to two orders of magnitude. This is implemented in an updated version of our PowerFit package for fast rigid body fitting in cryo-EM data, which can be freely downloaded from https://www.github.com/haddocking/powerfit.…”

Section: Introductionmentioning

confidence: 99%

Defining the limits and reliability of rigid-body fitting in cryo-EM maps using multi-scale image pyramids

Zundert

Bonvin

2016

Journal of Structural Biology

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. Defining the limits and reliability of rigid-body fitting in cryo-EM maps using multi-scale image pyramids. J. Struct. Biol., 195, 252-258 (2016).https://doi.org/10. 1016/j.jsb.2016.06.011 Defining the limits and reliability of rigid-body fitting in cryo-EM maps using multi-scale image pyramids Keywords1Cross correlation; PowerFit; Ribosome; Fisher z-transformation; Core-weighted; Modeling. AbstractCryo-electron microscopy provides fascinating structural insight into large macromolecular machines at increasing detail. Despite significant advances in the field, the resolution of the resulting three-dimensional images is still typically insufficient for de novo model building.To bridge the resolution gap and give an atomic interpretation to the data, high-resolution models are typically placed into the density as rigid bodies. Unfortunately, this is often done manually using graphics software, a subjective method that can lead to over-interpretation of the data. A more objective approach is to perform an exhaustive cross-correlation-based search to fit subunits into the density. Here we show, using five experimental ribosome maps ranging in resolution from 5.5 to 6.9Å, that cross-correlation-based fitting is capable of successfully fitting subunits correctly in the density for over 90% of the cases. Importantly, we provide indicators for the reliability and ambiguity of a fit, using the Fisher ztransformation and its associated confidence intervals, giving a formal approach to identify over-interpreted regions in the density. In addition, we quantify the resolution requirement for a successful fit as a function of the subunit size. For larger subunits the resolution of the data can be down-filtered to 20Å while still retaining an unambiguous fit. We leverage this information through the use of multi-scale image pyramids to accelerate the search up to 30-fold on CPUs and 40-fold on GPUs at a negligible loss in success rate. We implemented this approach in our rigid-body fitting software PowerFit, which can be freely downloaded from https://github.com/haddocking/powerfit.

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Section: Introductionmentioning

confidence: 99%

Defining the limits and reliability of rigid-body fitting in cryo-EM maps using multi-scale image pyramids

Zundert

Bonvin

2016

Journal of Structural Biology

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“…The slope of a graphic f(x, y) in the site (x,y) is given by the 2 dimensional ray vector [4], [19], [22].…”

Section: Derivative Gradient Filtermentioning

confidence: 99%

Limits those are invisible to be disclosed by using new imageprocessing Techniques

Goyal¹,

Verma²,

Mishra³

2017

IJISSE

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“…3D vision is an area of computer vision that has been widely studied [3][4][8][9]. A large number of methods have been proposed for this purpose.…”

Section: D Visionmentioning

confidence: 99%

Multimodal fusion system for NDT and Metrology

Verney¹,

Akhloufi²,

Aubreton³

2014

Proceedings of the 2014 International Conference on Quantitative InfraRed Thermography

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Abstract3D scanning and modeling is used in a wide range of applications like manufacturing, aerospace, security, biomedicine, etc. This kind of systems allows the scanning of a 3D point cloud that can be meshed and rendered in order to obtain a complete 3D model. However, 3D vision cannot detect subsurface defects. This later can be achieved using other imaging modalities, like thermal infrared imaging. This modality is very popular in non-destructive testing and visual inspection. In this work, we present a multi-modal fusion framework for combining these two modalities. We present an approach for a robotic inspection system integrating the proposed framework for 3D-NDT multimodal control and analysis.

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An Introduction to 3D Computer Vision Techniques and Algorithms

Cited by 251 publications

References 0 publications

Defining the limits and reliability of rigid-body fitting in cryo-EM maps using multi-scale image pyramids

Defining the limits and reliability of rigid-body fitting in cryo-EM maps using multi-scale image pyramids

Limits those are invisible to be disclosed by using new imageprocessing Techniques

Multimodal fusion system for NDT and Metrology

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