Pose estimation using local structure-specific shape and appearance context

Buch, Anders Glent; Kraft, Dirk; Kämäräinen, Joni-Kristian; Petersen, Henrik Gordon; Krüger, Norbert

doi:10.1109/icra.2013.6630856

Cited by 65 publications

(50 citation statements)

References 29 publications

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“…Most of the processing steps use generally applicable procedures available in open-source libraries and software, including registration, cleaning, and meshing of the point clouds (Cignoni et al, 2008;Rusu and Cousins, 2011;Buch et al, 2013;Kazhdan and Hoppe, 2013). General solutions for the segmentation of features like leaves and stems from plants, however, remain less developed, especially for 3D plant representations (Paproki et al, 2012;Paulus et al, 2013;Xia et al, 2015).…”

Section: D Sorghum Reconstructions From Depth Imagesmentioning

confidence: 99%

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

2016

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Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height, leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.

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Section: D Sorghum Reconstructions From Depth Imagesmentioning

confidence: 99%

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

2016

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“…We used two complementary representations of objects in these tests, namely the texlet-based context descriptors first presented in [9] as well as the line segment-based context descriptors presented in [7]. Note that for the line segments, the absolute number of features computed in an object view is fairly low.…”

Section: Methodsmentioning

confidence: 99%

Using surfaces and surface relations in an Early Cognitive Vision system

Kraft

Mustafa

Popovic

et al. 2015

Machine Vision and Applications

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We present a deep hierarchical visual system with two parallel hierarchies for edge and surface information. In the two hierarchies, complementary visual information is represented on different levels of granularity together with the associated uncertainties and confidences. At all levels geometric and appearance information is coded explicitly in 2D and 3D allowing to access this information separately and to link between the different levels. We demonstrate the advantages of such hierarchies in three applications covering grasping, view-point independent object representation, and pose estimation.

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“…Then, keypoints were extracted and the local feature descriptor of each keypoint was calculated for matching. Keypoint correspondence was obtained by matching the features, and false matchings were discarded by considering geometric constraints like the one in the study by Buch et al [11]. Once the correspondence of the keypoints between the two point clouds was obtained, a coarse transformation between them was calculated.…”

Section: Methodsmentioning

confidence: 99%

“…A correspondence grouping method was implemented, as described in the study by Buch et al [11], to discard false correspondences based on geometric consistency. Figure 2(b,c) show the results of keypoint matching before and after discarding false correspondences in the registration of a head phantom.…”

Section: Matching and Discarding False Correspondencesmentioning

confidence: 99%

See 1 more Smart Citation

A new robust markerless method for automatic image-to-patient registration in image-guided neurosurgery system

Liu

Song

Wang

2017

Computer Assisted Surgery

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Background: Compared with the traditional point-based registration in the image-guided neurosurgery system, surface-based registration is preferable because it does not use fiducial markers before image scanning and does not require image acquisition dedicated for navigation purposes. However, most existing surface-based registration methods must include a manual step for coarse registration, which increases the registration time and elicits some inconvenience and uncertainty. Methods: A new automatic surface-based registration method is proposed, which applies 3D surface feature description and matching algorithm to obtain point correspondences for coarse registration and uses the iterative closest point (ICP) algorithm in the last step to obtain an image-to-patient registration. Results: Both phantom and clinical data were used to execute automatic registrations and target registration error (TRE) calculated to verify the practicality and robustness of the proposed method. In phantom experiments, the registration accuracy was stable across different downsampling resolutions (18-26 mm) and different support radii (2-6 mm). In clinical experiments, the mean TREs of two patients by registering full head surfaces were 1.30 mm and 1.85 mm. Conclusion: This study introduced a new robust automatic surface-based registration method based on 3D feature matching. The method achieved sufficient registration accuracy with different real-world surface regions in phantom and clinical experiments.

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Pose estimation using local structure-specific shape and appearance context

Cited by 65 publications

References 29 publications

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

Using surfaces and surface relations in an Early Cognitive Vision system

A new robust markerless method for automatic image-to-patient registration in image-guided neurosurgery system

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