Visual Odometry for RGB-D Cameras

Fontes, Afonso; Maia, José Everardo Bessa

doi:10.48550/arxiv.2203.15119

Cited by 1 publication

(2 citation statements)

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“…The pixel brightness is also assumed not to change significantly on those two consecutive frames. [8], other defines correspondence on pairs or tuples of points [9]. When candidate correspondence are collected, alignment is estimated attractively from sparse subset to correspondence.…”

Section: Introductionmentioning

confidence: 99%

“…When candidate correspondence are collected, alignment is estimated attractively from sparse subset to correspondence. This iterative process is typically based on variant of randomized algorithms like RANSAC [8], [9]. When the data is noisy and the surfaces only partially overlap, existing pipelines often require many iterations to sample a good correspondence set and find a good reasonable alignment.…”

Section: Introductionmentioning

confidence: 99%

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A Modified ICP Algorithm Based on FAST and Optical Flow for 3D Registration

Koniarski¹,

Myśliński²

2022

Annals of Computer Science and Information Systems

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This paper presents a modified Iterative Closest Point (ICP) algorithm based on a suitable selection of initial points and local optical flow to speed up registration of static scenes with high accuracy. The biggest disadvantages of using standard ICP algorithm are appropriate initialization and effective matching point step in each iteration. In the proposed modification we deal with these problems and optimize this method for Augmented Reality application. As this application uses RGB-D images sequence the changes between consecutive key-frames are small. Therefore only small subset of the source image key-points is selected using scale-space pyramid and FAST approaches. It leads to the significant reduction of the number of the processed image points. Since the point matching technique using local optical flow is applied, in each optimization step of ICP the costly point matching procedure can be abandoned. The proposed approach has been validated by the numerical examples.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%