Camera array synthetic aperture focusing and fusion based hidden object imaging
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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Acquiring dynamic 3D fluid surfaces is a challenging problem in computer vision. Single or stereo camera based solutions are sensitive to refraction distortions, fast fluid motions, and calibration errors. In this paper, we present a multi-view based solution for robustly capturing fast evolving fluid wavefronts. We first construct a portable, 3脳3 camera array system as the main acquisition device. We elaborately design the system to allow high-resolution and high-speed capture. To recover fluid surfaces, we place a known pattern beneath the surface and position the camera array on top to observe the pattern. By tracking the distorted feature points over time and across cameras, we obtain spatial-temporal correspondence maps and we use them for specular carving to reconstruct the time-varying surface. In case one of the cameras loses track due to distortions or blurs, we use the rest of the cameras to construct the surface and then apply multi-perspective warping to locate the lost-track feature points so that we can continue using the camera in later frames. Our experiments on synthetic and real data demonstrate that our multi-view framework is robust and reliable.