Face Detection and Verification Using Lensless Cameras
Published in IEEE Transactions on Computational Imaging (TCI), 2018
Abstract: Lensless imaging systems, such as the recently proposed FlatCam, offer numerous advantages over lens-based systems such as a thin form-factor, low cost, and higher light throughput. However, little work has been done in analyzing these systems’ depth of field characteristics. A depth-dependent calibration step is necessary to obtain the image from the FlatCam measurements, and this calibration determines the system’s depth of field. In this paper, we characterize the FlatCam’s depth of field properties and show that (a) for scene depths on the order of tens of centimeters, it is possible to perform depth-selective refocusing from a single captured image and (b) for sufficiently large scene depths, calibratin.g for one depth can provide a very large depth of field.