3D scene reconstruction from multi-aperture images

Miao Mao; Kaihuai Qin

doi:10.1117/12.2064403

16 April 2014 3D scene reconstruction from multi-aperture images

Miao Mao, Kaihuai Qin

Proceedings Volume 9159, Sixth International Conference on Digital Image Processing (ICDIP 2014); 91591E (2014) https://doi.org/10.1117/12.2064403
Event: Sixth International Conference on Digital Image Processing, 2014, Athens, Greece

Abstract

With the development of virtual reality, there is a growing demand for 3D modeling of real scenes. This paper proposes a novel 3D scene reconstruction framework based on multi-aperture images. Our framework consists of four parts. Firstly, images with different apertures are captured via programmable aperture. Secondly, we use SIFT method for feature point matching. Then we exploit binocular stereo vision to calculate camera parameters and 3D positions of matching points, forming a sparse 3D scene model. Finally, we apply patch-based multi-view stereo to obtain a dense 3D scene model. Experimental results show that our method is practical and effective to reconstruct dense 3D scene.

Citation Download Citation

Miao Mao and Kaihuai Qin "3D scene reconstruction from multi-aperture images", Proc. SPIE 9159, Sixth International Conference on Digital Image Processing (ICDIP 2014), 91591E (16 April 2014); https://doi.org/10.1117/12.2064403

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