Abstract
Due to hardware limitations, existing light field (LF) capturing devices cannot offer sufficient field of view for building 6 degrees of freedom (6 DOF) VR applications. LF image stitching methods can be used to address this problem. The state-of-the-art LF stitching methods highly depend on the stitching accuracy of center view which is essentially a 2D image stitching task. However, conventional 2D image stitching methods usually suffer from the ghosting artifacts. In this paper, a None Ghosting Artifacts (NGA) stitching method is proposed to tackle this problem. We theoretically reveal the intrinsic cause of the ghosting artifacts and then further verify that different depth scenes require different homography matrices for warping. Therefore, the clustered depth map is employed to segment the scene into several layers, and the layer-specific homography matrix is computed for warping. An interpolation mechanism is also proposed to ensure that each layer has its own transformation. Compared with state-of-the-art stitching methods aiming to alleviate ghosting artifacts, experimental results show that the proposed method not only stitches images without ghosting artifacts, but also achieves realistic perspective transformation.
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Acknowledgements
This work was supported in part by the National Key Research and Development Program of China under Grant No. 2016YFC0801001, the National Program on Key Basic Research Projects (973 Program) under Grant 2015CB351803, NSFC under Grant 61571413, 61632001,61390514, and Intel ICRI MNC.
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Zhang, W., Zhao, S., Zhou, W., Chen, Z. (2018). None Ghosting Artifacts Stitching Based on Depth Map for Light Field Image. In: Hong, R., Cheng, WH., Yamasaki, T., Wang, M., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2018. PCM 2018. Lecture Notes in Computer Science(), vol 11164. Springer, Cham. https://doi.org/10.1007/978-3-030-00776-8_52
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