Depth extraction of 3D objects using axially distributed image sensing

Suk-Pyo Hong,Donghak Shin,Eun-Soo Kim,Byung-Gook Lee

doi:10.1364/oe.20.023044

Abstract

Axially distributed image sensing (ADS) technique is capable of capturing 3D objects and reconstructing high-resolution slice plane images for 3D objects. In this paper, we propose a computational method for depth extraction of 3D objects using ADS. In the proposed method, the high-resolution elemental images are recorded by simply moving the camera along the optical axis and the recorded elemental images are used to generate a set of 3D slice images using the computational reconstruction algorithm based on ray back-projection. To extract depth of 3D object, we propose the simple block comparison algorithm between the first elemental image and a set of 3D slice images. This provides a simple computation process and robustness for depth extraction. To demonstrate our method, we carry out the preliminary experiments of three scenarios for 3D objects and the results are presented. To our best knowledge, this is the first report to extract the depth information using an ADS method.

Highlights

Acquiring depth information from three-dimensional (3D) objects in real world is an important issue in many diverse fields of computer vision, 3D display and 3D recognition
A simple modification structure of synthetic aperture integral imaging (SAII) was proposed. This is called an axially distributed image sensing (ADS) method [8,22–24], in which longitudinal perspective information is obtained by translating a camera along its optical axis
The high-resolution elemental images recorded from ADS can be used for acquiring high-resolution depth information of real-world 3D objects

Summary

Introduction

Acquiring depth information from three-dimensional (3D) objects in real world is an important issue in many diverse fields of computer vision, 3D display and 3D recognition. The recorded elemental images have low-resolution so that the extracted depth is poor To overcome this problem, synthetic aperture integral imaging (SAII) was proposed [18–21], in which the multiple cameras or moving cameras are used to acquire depth information. A simple modification structure of SAII was proposed This is called an axially distributed image sensing (ADS) method [8,22–24], in which longitudinal perspective information is obtained by translating a camera along its optical axis. The proposed depth extraction is implemented by simple summation of elemental images and comparison of intensity distribution between blocks from first elemental image and slice plane images This can avoid the complex corresponding search process in the conventional depth extraction algorithm. To show the usefulness of the proposed method, we carry out the preliminary experiments of 3D objects and the results are presented

ADS pickup

Slice image reconstruction using the recorded elemental images

Depth extraction process

Depth accuracy in ADS

Experiments and results

Conclusion