混合相机的高速深度流生成

X. Zuo, Sen Wang, Jiangbin Zheng, Ruigang Yang
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引用次数: 3

摘要

高速视频已普遍应用于消费级相机,用相应的深度流增强这些视频将实现新的多媒体应用,如3D慢动作视频。在本文中,我们提出了一种混合相机系统,该系统将高速彩色相机与深度传感器(例如Kinect深度传感器)相结合,以产生可以产生高速和高分辨率RGB+深度流的深度流。简单地插值低速深度帧是不满意的,其中插值伪影和丢失的表面细节往往是可见的。我们开发了一种新的框架,它利用了每帧内的阴影约束和相邻帧之间的光流约束。更具体地说,我们提出了(a)一种有效的方法来寻找本征图像,以允许更准确的正态估计;(b)基于优化的框架来估计高分辨率/高速深度流,考虑时间平滑性和阴影/深度一致性。我们用合成序列和真实序列评估了我们的整体框架,它比以前的最先进的技术表现出更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-speed Depth Stream Generation from a Hybrid Camera
High-speed video has been commonly adopted in consumer-grade cameras, augmenting these videos with a corresponding depth stream will enable new multimedia applications, such as 3D slow-motion video. In this paper, we present a hybrid camera system that combines a high-speed color camera with a depth sensor, e.g. Kinect depth sensor, to generate a depth stream that can produce both high-speed and high-resolution RGB+depth stream. Simply interpolating the low-speed depth frames is not satisfactory, where interpolation artifacts and lose in surface details are often visible. We have developed a novel framework that utilizes both shading constraints within each frame and optical flow constraints between neighboring frames. More specifically we present (a) an effective method to find the intrinsics images to allow more accurate normal estimation; and (b) an optimization-based framework to estimate the high-resolution/high-speed depth stream, taking into consideration temporal smoothness and shading/depth consistency. We evaluated our holistic framework with both synthetic and real sequences, it showed superior performance than previous state-of-the-art.
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