Deep360Up:一种基于深度学习的VR图像垂直自动调整方法

Raehyuk Jung, Aiden Seung Joon Lee, Amirsaman Ashtari, J. Bazin
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引用次数: 20

摘要

球形VR相机可以拍摄360°视野的高质量沉浸式VR图像。然而,在实际应用中,当摄像机的方向不垂直时,获取的VR图像在VR头显上显示时会出现倾斜,从而降低了VR体验的质量。为了克服这个问题,我们提出了一种基于深度学习的方法,可以自动估计VR图像的方向并返回其垂直版本。与现有的方法相比,我们的方法不需要在图像中存在线或地平线,因此可以应用于广泛的场景。广泛的实验和与最先进的方法的比较成功地证实了我们的方法的有效性。
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Deep360Up: A Deep Learning-Based Approach for Automatic VR Image Upright Adjustment
Spherical VR cameras can capture high-quality immersive VR images with a 360° field of view. However, in practice, when the camera orientation is not straight, the acquired VR image appears tilted when displayed on a VR headset, which diminishes the quality of the VR experience. To overcome this problem, we present a deep learning-based approach that can automatically estimate the orientation of a VR image and return its upright version. In contrast to existing methods, our approach does not require the presence of lines or horizon in the image, and thus can be applied on a wide range of scenes. Extensive experiments and comparisons with state-of-the-art methods have successfully confirmed the validity of our approach.
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