Improved resolution 3D object sensing and recognition using time multiplexed computational integral imaging.

In this paper we present a high-resolution technique to passively sense, detect and recognize a 3D object using computational integral imaging. We show that the use of a non-stationary microlens array improves the longitudinal distance estimation quantization error. The proposed method overcomes the Nyquist upper limit for the resolution. We use 3D non-linear correlation to recognize the 3D coordinates and shape of the desired object.