3D Reconstruction of Plant/Tree Canopy Using Monocular and Binocular Vision

Zhijiang Ni,Won Lee,Thomas Burks

doi:10.3390/jimaging2040028

Abstract

Three-dimensional (3D) reconstruction of a tree canopy is an important step in order to measure canopy geometry, such as height, width, volume, and leaf cover area. In this research, binocular stereo vision was used to recover the 3D information of the canopy. Multiple images were taken from different views around the target. The Structure-from-motion (SfM) method was employed to recover the camera calibration matrix for each image, and the corresponding 3D coordinates of the feature points were calculated and used to recover the camera calibration matrix. Through this method, a sparse projective reconstruction of the target was realized. Subsequently, a ball pivoting algorithm was used to do surface modeling to realize dense reconstruction. Finally, this dense reconstruction was transformed to metric reconstruction through ground truth points which were obtained from camera calibration of binocular stereo cameras. Four experiments were completed, one for a known geometric box, and the other three were: a croton plant with big leaves and salient features, a jalapeno pepper plant with median leaves, and a lemon tree with small leaves. A whole-view reconstruction of each target was realized. The comparison of the reconstructed box’s size with the real box’s size shows that the 3D reconstruction is in metric reconstruction.

Highlights

Three-dimensional (3D) reconstruction of a plant/tree canopy can be used to measure the height, width, volume, area, and biomass of the target, and can be used to visualize the object in virtual 3D space. 3D reconstruction is called 3D digitizing or 3D modeling
A ball pivoting algorithm was used to do surface modeling to realize dense reconstruction. This dense reconstruction was transformed to metric reconstruction through ground truth points which were obtained from camera calibration of binocular stereo cameras
This paper demonstrated a new approach to calibrate the camera calibration matrix on a metric level and implemented the VisualSFM method to make a projective reconstruction of a plant/tree canopy

Summary

Introduction

Three-dimensional (3D) reconstruction of a plant/tree canopy can be used to measure the height, width, volume, area, and biomass of the target, and can be used to visualize the object in virtual 3D space. 3D reconstruction is called 3D digitizing or 3D modeling. Three-dimensional (3D) reconstruction of a plant/tree canopy can be used to measure the height, width, volume, area, and biomass of the target, and can be used to visualize the object in virtual 3D space. 3D reconstruction is called 3D digitizing or 3D modeling. Plant/tree 3D reconstruction could be cataloged into two types: (1) depth-based 3D modeling; and (2) image-based. Sinoquet et al [1] created a 3D model of corn plant profiles and canopy structure. The 3D results were used to calculate the leaf area and its distribution in the plant. Tumbo et al [2] used ultrasonics in the field to measure citrus canopy volume. Twenty ultrasonic transducers were arranged on vertical boards (10 sensors per side). A formula was provided to calculate the volume. To study the accuracy of this calculation, Zaman and Salyani [3]

Methods

Results

Conclusion