Comparing different metrics on an anisotropic depth completion model

Author:

Lazcano Vanel1,Calderero Felipe2,Ballester Coloma3

Affiliation:

1. Universidad Mayor, Santiago, Chile

2. Sandoz Farmacéutica, Madrid, Spain

3. Universitat Pompeu Fabra, Barcelona, Spain

Abstract

This paper discussed an anisotropic interpolation model that filling in-depth data in a largely empty region of a depth map. We consider an image with an anisotropic metric gi⁢j that incorporates spatial and photometric data. We propose a numerical implementation of our model based on the “eikonal” operator, which compute the solution of a degenerated partial differential equation (the biased Infinity Laplacian or biased Absolutely Minimizing Lipschitz Extension). This equation’s solution creates exponential cones based on the available data, extending the available depth data and completing the depth map image. Because of this, this operator is better suited to interpolating smooth surfaces. To perform this task, we assume we have at our disposal a reference color image and a depth map. We carried out an experimental comparison of the AMLE and bAMLE using various metrics with square root, absolute value, and quadratic terms. In these experiments, considered color spaces were sRGB, XYZ, CIE-L*⁢a*⁢b*, and CMY. In this document, we also presented a proposal to extend the AMLE and bAMLE to the time domain. Finally, in the parameter estimation of the model, we compared EHO and PSO. The combination of sRGB and square root metric produces the best results, demonstrating that our bAMLE model outperforms the AMLE model and other contemporary models in the KITTI depth completion suite dataset. This type of model, such as AMLE and bAMLE, is simple to implement and represents a low-cost implementation option for similar applications.

Publisher

IOS Press

Reference26 articles.

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3. Extension of functions satisfyng Lipschitz conditions;Aronsson;Aktiv fuer Mathematik,1967

4. On the partial differential equation ux2⁢ux⁢x+2⁢ux⁢uy⁢ux⁢y+uy2⁢uy⁢y=0;Aronsson;Aktiv fuer Matematik,1968

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2. Hybrid Model Convolutional Stage-Positive Definite Metric Operator-Infinity Laplacian Applied to Depth Completion;2022 Tenth International Symposium on Computing and Networking Workshops (CANDARW);2022-11

3. Biased-Infinity Laplacian Applied to Depth Completion Using a Balanced Anisotropic Metric;Lecture Notes in Electrical Engineering;2022

4. Hybrid Pipeline Infinity Laplacian Plus Convolutional Stage Applied to Depth Completion;Computational Vision and Bio-Inspired Computing;2022

5. Biased-Infinity Laplacian Applied to Depth Completion Using a Balanced Anisotropic Metric;Lecture Notes in Electrical Engineering;2022

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