Perspective-consistent multifocus multiview 3D reconstruction of small objects

TL;DR

This paper introduces a novel perspective-consistent multifocus multiview 3D reconstruction method for small objects, addressing limitations of traditional techniques by incorporating fixed-lens capture and calibration to improve accuracy and reduce artifacts.

Contribution

The paper proposes a new fixed-lens multifocus capture and calibration approach that enhances 3D reconstruction accuracy for small objects by considering scale and shift issues.

Findings

Camera poses are at least 3 times less noisy with the proposed method.

The new approach effectively reduces artifacts in in-focus images.

Initial experiments confirm improved reconstruction quality.

Abstract

Image-based 3D reconstruction or 3D photogrammetry of small-scale objects including insects and biological specimens is challenging due to the use of high magnification lens with inherent limited depth of field, and the object's fine structures and complex surface properties. Due to these challenges, traditional 3D reconstruction techniques cannot be applied without suitable image pre-processings. One such preprocessing technique is multifocus stacking that combines a set of partially focused images captured from the same viewing angle to create a single in-focus image. Traditional multifocus image capture uses a camera on a macro rail. Furthermore, the scale and shift are not properly considered by multifocus stacking techniques. As a consequence, the resulting in-focus images contain artifacts that violate perspective image formation. A 3D reconstruction using such images will fail to produce an accurate 3D model of the object. This paper shows how this problem can be solved effectively by a new multifocus stacking procedure which includes a new Fixed-Lens Multifocus Capture and camera calibration for image scale and shift. Initial experimental results are presented to confirm our expectation and show that the camera poses of fixed-lens images are at least 3-times less noisy than those of conventional moving lens images.