Real-Time visual loop-closure detection using fused iterative close point algorithm and extended Kalman filter

Vokhmintcev, A. V.; Timchenko, M.; Alina, K.

doi:10.1109/icieam.2017.8076187

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…Для вариационной задачи точка-плоскость в классе аффинных преобразований найдены решения в замкнутой форме [11]. Устойчивость построения трёхмерной карты поверхности достигается глобаль-ДОКЛАДЫ АКАДЕМИИ НАУК том 484 № 6 2019 ной оптимизацией графа положений камеры с помощью алгоритма проверки возврата камеры в ранее пройденную точку [12].…”

Section: информатикаunclassified

“…В работе был проведён сравнительный анализ точных и приближённых решений вариационной задачи на эталонных базах данных. Нами были проведены эксперименты на базах данных изображений ALOI и Indoor Segmentation and Support Inference (ECCV) [4,12,13]. Было установлено, что приближённые методы решения позволяют получить достаточно точные результаты при реконструкции трёхмерных сцен окружающего пространства.…”

Section: схема построения трёхмерной модели сценыunclassified

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Reconstruction of three-dimensional maps based on closed-form solutions of the variational problem of multisensor data registration

Vokhmintcev¹,

Melnikov²,

Mironov³

et al. 2019

Доклады Академии наук

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A closed-form solution is proposed for the problem of minimizing a functional consisting of two terms measuring mean-square distances for visually associated characteristic points on an image and meansquare distances for point clouds in terms of a point-to-plane metric. An accurate method for reconstructing three-dimensional dynamic environment is presented, and the properties of closed-form solutions are described. The proposed approach improves the accuracy and convergence of reconstruction methods for complex and large-scale scenes.

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Section: информатикаunclassified

Section: схема построения трёхмерной модели сценыunclassified

Reconstruction of three-dimensional maps based on closed-form solutions of the variational problem of multisensor data registration

Vokhmintcev¹,

Melnikov²,

Mironov³

et al. 2019

Доклады Академии наук

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Multi-Scale Upsampling GAN Based Hole-Filling Framework for High-Quality 3D Cultural Heritage Artifacts

et al. 2022

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With the rapid development of 3D scanners, the cultural heritage artifacts can be stored as a point cloud and displayed through the Internet. However, due to natural and human factors, many cultural relics had some surface damage when excavated. As a result, the holes caused by these damages still exist in the generated point cloud model. This work proposes a multi-scale upsampling GAN (MU-GAN) based framework for completing these holes. Firstly, a 3D mesh model based on the original point cloud is reconstructed, and the method of detecting holes is presented. Secondly, the point cloud patch contains hole regions and is extracted from the point cloud. Then the patch is input into the MU-GAN to generate a high-quality dense point cloud. Finally, the empty areas on the original point cloud are filled with the generated dense point cloud patches. A series of real-world experiments are conducted on real scan data to demonstrate that the proposed framework can fill the holes of 3D heritage models with grained details. We hope that our work can provide a useful tool for cultural heritage protection.

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Real-Time visual loop-closure detection using fused iterative close point algorithm and extended Kalman filter

Cited by 2 publications

References 33 publications

Reconstruction of three-dimensional maps based on closed-form solutions of the variational problem of multisensor data registration

Reconstruction of three-dimensional maps based on closed-form solutions of the variational problem of multisensor data registration

Multi-Scale Upsampling GAN Based Hole-Filling Framework for High-Quality 3D Cultural Heritage Artifacts

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