English

Toward Depth Estimation Using Mask-Based Lensless Cameras

Computer Vision and Pattern Recognition 2017-11-10 v1

Abstract

Recently, coded masks have been used to demonstrate a thin form-factor lensless camera, FlatCam, in which a mask is placed immediately on top of a bare image sensor. In this paper, we present an imaging model and algorithm to jointly estimate depth and intensity information in the scene from a single or multiple FlatCams. We use a light field representation to model the mapping of 3D scene onto the sensor in which light rays from different depths yield different modulation patterns. We present a greedy depth pursuit algorithm to search the 3D volume and estimate the depth and intensity of each pixel within the camera field-of-view. We present simulation results to analyze the performance of our proposed model and algorithm with different FlatCam settings.

Keywords

Cite

@article{arxiv.1711.03527,
  title  = {Toward Depth Estimation Using Mask-Based Lensless Cameras},
  author = {M. Salman Asif},
  journal= {arXiv preprint arXiv:1711.03527},
  year   = {2017}
}
R2 v1 2026-06-22T22:41:21.546Z