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Falah-Jabar-Rahim/Globally-and-Locally-Adapted-Pannini-Projection-v1

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Introduction

Python implementation of globally and locally adapted Pannini projection (GLA-PP). GLA-PP is a content-aware sphere to plane projection proposed in [1] for viewport rendering of omnidirectional images; it is based on Pannini projection proposed in [2]. This projection was developed to improve the performance of globally adapted Pannini projection (GA-PP) proposed in [3]. GA-PP is globally adapted to the viewport content (i.e., the projection parameters d and vc have the same values for the whole viewport), therefore the geometric distortions such as stretching of objects and/or bending of straight lines may be still visible for some image regions and structures. In GLA-PP, the projection parameters are allowed to vary locally, and thus geometric distortions are further reduced, especially for the foreground objects. GLA-PP is used the similar mesh optimization procedure as in [4]. Refer to [3] and [1] for more details on GA-PP and GLA-PP respectively.

Installation

  • Python >= 3.6
  • PyTorch >= 1.6 with correct torchvision

Its recommended to create a virtual environment with Anaconda:
Install pytorch conda install pytorch==1.6.0 torchvision -c pytorch
Install other dependencies pip install -r requirements.txt

Usage

Run main.py for demo

Note

This version dose not include GA-PP projection, instead, the projection parameters, d, vc are fixed, d=0.5, vc=0.6. GA-PP will be included soon.

References

[1] F. Jabar, J. Ascenso, and M.P. Queluz, “Globally and Locally Optimized Pannini Projection for Viewport Rendering of 360° Images”, Submitted to J. Vis. Commun. Image Represent., Oct. 2022
[2] T. K.Sharpless, B. Postle, and D. M.German, “Pannini : A New Projection for Rendering Wide Angle Perspective Images,” in Proc. of the 6th Int. Conf. on Computational Aesthetics in Graphics, Visualization and Imaging, London, United Kingdom, Jul. 2010.
[3] F. Jabar, J. Ascenso, and M.P. Queluz “Object-Based Geometric Distortion Metric for Viewport Rendering of 360⸰ Images”, IEEE Access, vol. 10, pp. 13827-13843, Jan. 2022.
[4] Y. Shih, W. Lai, and C. Liang, “Distortion-Free Wide-Angle Portraits on Camera Phones,” ACM Trans. Graph., vol. 38, no. 4, pp. 1–12, Jul. 2019.

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