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Papers

altiro3D: Scene representation from single image and novel view synthesis

2023-04-02 · E. Canessa, L. Tenze

We introduce altiro3D, a free extended library developed to represent reality starting from a given original RGB image or flat video. It allows to generate a light-field (or Native) image or video and get a realistic 3D experience. To synthesize N-number of virtual images and add them sequentially into a Quilt collage, we apply MiDaS models for the monocular depth estimation, simple OpenCV and Telea inpainting techniques to map all pixels, and implement a 'Fast' algorithm to handle 3D projection camera and scene transformations along N-viewpoints. We use the degree of depth to move proportionally the pixels, assuming the original image to be at the center of all the viewpoints. altiro3D can also be used with DIBR algorithm to compute intermediate snapshots from a equivalent 'Real (slower)' camera with N-geometric viewpoints, which requires to calibrate a priori several intrinsic and extrinsic camera parameters. We adopt a pixel- and device-based Lookup Table to optimize computing time. The multiple viewpoints and video generated from a single image or frame can be displayed in a free-view LCD display.

📄 PDF Abstract BibTeX arXiv:2304.11161

Code (1)

canessae/altiro3D 공식 구현

Tasks

Depth EstimationMonocular Depth EstimationNovel View Synthesis

Methods 이 논문이 사용한 방법론

Library 설명 없음
Inpainting Train a convolutional neural network to generate the contents of an arbitrary image region conditioned on its surroundings.

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