Depth from defocus applied to auto focus
S Yasugi, K Nguyen, K Ezawa… - 2014 IEEE 3rd Global …, 2014 - ieeexplore.ieee.org
S Yasugi, K Nguyen, K Ezawa, T Kawamura
2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE), 2014•ieeexplore.ieee.orgDepth from Defocus (DFD) is known as the technology which is able to estimate depth in the
scene by a monocular camera without any additive devices. Using this advantage of DFD,
we improved the speed of Auto Focus (AF). To apply DFD to AF, it is necessary to capture 2
images that have a small amount of “difference in focal positions”(we call DiFP). In this
paper, we show the performance of the depth estimation when the DiFP is changed, and
verify that Low Pass Filter is a good solution to get robust depth.
scene by a monocular camera without any additive devices. Using this advantage of DFD,
we improved the speed of Auto Focus (AF). To apply DFD to AF, it is necessary to capture 2
images that have a small amount of “difference in focal positions”(we call DiFP). In this
paper, we show the performance of the depth estimation when the DiFP is changed, and
verify that Low Pass Filter is a good solution to get robust depth.
Depth from Defocus (DFD) is known as the technology which is able to estimate depth in the scene by a monocular camera without any additive devices. Using this advantage of DFD, we improved the speed of Auto Focus (AF). To apply DFD to AF, it is necessary to capture 2 images that have a small amount of “difference in focal positions” (we call DiFP). In this paper, we show the performance of the depth estimation when the DiFP is changed, and verify that Low Pass Filter is a good solution to get robust depth.
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