Minimization of Point Light Source Coordinates Determination Error on Photo Detectors

Kruzhilov, Ivan

doi:10.1515/joc.2011.037

Cited by 3 publications

(2 citation statements)

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“…The same method is used when estimating star projection center for the satellite attitude estimation [9]. If corners heat maps estimation had a Gaussian distribution equal to their ground truth, then the maximum likelihood method [9] would be more efficient. However, in our case output corner heat maps are far from being Gaussian (e.g.…”

Section: Key Points Coordinate Estimationmentioning

confidence: 99%

Double Refinement Network for Room Layout Estimation

Kruzhilov¹,

Romanov²,

Konushin³

2019

Preprint

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Layout estimation is a challenge of segmenting a cluttered room image into floor, walls and ceiling. We applied Double refinement network proved to be efficient in the depth estimation to generate heat maps for room key points and edges. Our method is the first not using encoder-decoder architecture for the room layout estimation. ResNet50 was utilized as a backbone for the network instead of VGG16 commonly used for the task, allowing the network to be more compact and faster. We designed a special layout score function and layout ranking algorithm for key points and edges output. Our method achieved the lowest pixel and corner errors on the LSUN data set. The input image resolution is 224*224.

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Section: Key Points Coordinate Estimationmentioning

confidence: 99%

Double Refinement Network for Room Layout Estimation

Kruzhilov¹,

Romanov²,

Konushin³

2019

Preprint

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“…Light from stars is passing through the optical path of the device and is projected on a photodetector. Using special algorithms, 3,4 stars are segregated on the background of photodetector noise and optical distortions, and their directional cosines are determined in the star tracker reference system.…”

Section: Introductionmentioning

confidence: 99%

Small-angle rotation method for star tracker orientation

Kruzhilov

2013

J. Appl. Remote Sens

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The Wahba problem is the task of constrained optimization seeking the matrix from SO(3), which maximally converges (based on the least squares criterion) two sequences of unit vectors. The solution of this task is vital for satellite attitude determination using star trackers. An iterative method for solving the Wahba problem is proposed. Each iteration of the proposed method is reduced to sequential rotation of the vectors and solving the system of linear algebraic equations. Usage of the method implies that the corresponding vectors of both sequences are located sufficiently close to each other. Two variants of the method are proposed, having linear and quadratic convergence. The Wahba problem solution is interpreted in terms of finding the angular velocity of a system of material points, which have certain angular momentum. Taking into consideration the characteristics of state-of-the-art star trackers, one to two iterations are sufficient for finding the optimal solution using the small-angle rotation method. The primary advantage of the proposed method as compared with classical methods based on calculation of eigenvectors and singular decomposition is the simplicity of its implementation. © The Authors.Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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