主动视觉的最大似然离焦深度

W. Klarquist, W. Geisler, A. Bovik
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引用次数: 32

摘要

介绍了一种利用图像离焦主动恢复深度信息的新方法,该方法通过提供单目深度估计来指导相机定位进行立体处理,从而支持主动立体视觉深度恢复。这种主动离焦深度方法采用图像离焦的空间频率模型,该模型结合了图像采集系统的光学传递函数和最大似然估计器,以确定从相同姿势拍摄的两幅或多幅图像序列中存在的离焦量。这种离焦估计被转化为深度和相关不确定性的测量,用于控制可变基线立体相机系统的定位。这种协同安排大大降低了立体对应过程的匹配不确定性,提高了主动立体视觉平台可获得的深度分辨率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maximum-likelihood depth-from-defocus for active vision
A new method for actively recovering depth information using image defocus is demonstrated and shown to support active stereo vision depth recovery by providing monocular depth estimates to guide the positioning of cameras for stereo processing. This active depth-from-defocus approach employs a spatial frequency model for image defocus which incorporates the optical transfer function of the image acquisition system and a maximum likelihood estimator to determine the amount of defocus present in a sequence of two or more images taken from the same pose. This defocus estimate is translated into a measurement of depth and associated uncertainty that is used to control the positioning of a variable baseline stereo camera system. This cooperative arrangement significantly reduces the matching uncertainty of the stereo correspondence process and increases the depth resolution obtainable with an active stereo vision platform.
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