Realistic Object Reconstruction Under Different Depths Through Light Field Imaging for Virtual Reality
Ali Mehmood Khan, Md. Moinul Hossain, Alexandra Covaci, Konstantinos Sirlantzis, Qi Qi · IET Image Processing · 2025
ABSTRACT Virtual reality (VR) immerses users in digital environments and is used in various applications. VR content is created using either computer‐generated or conventional imaging. However, conventional imaging captures only 2D spatial information, which limits the realism of VR content. Advanced technologies like light field (LF) imaging can overcome this limitation by capturing both 2D spatial and 2D angular information in 4D LF images. This paper proposes a depth reconstruction model through LF imaging to aid in creating realistic VR content. Comprehensive calibrations are performed, including adjustments for camera parameters, depth calibration, and field of view (FOV) estimation. Aberration corrections, like distortion and vignetting effect correction, are conducted to enhance the quality of the reconstruction. To achieve realistic scene reconstruction, experiments were conducted by setting up a scenario with multiple objects positioned at three different depths. Quality assessments were carried out to evaluate the reconstruction quality across these varying depths. The results demonstrate that depth reconstruction quality improves with the proposed method. It also indicates that the model reduces LF image size and processing time. The depth images reconstructed by the proposed model have the potential to generate realistic VR content and can also facilitate the integration of refocusing capabilities within VR environments.