Comparative evaluation of incremental and global SfM-MVS pipelines for 3D reconstruction of peanut plants: implications for viewpoint configuration and image preprocessing

Abstract

Three-dimensional (3D) reconstruction based on structure from motion and multi-view stereo (SfM-MVS) is increasingly used in plant phenotyping, but its performance is influenced by crop architecture, viewpoint configuration, and image preprocessing. For compact crops such as peanut, dense branching and severe within-canopy occlusion make reliable reconstruction challenging. This study evaluated the effects of reconstruction pipeline, angular interval, and image preprocessing on 3D reconstruction of peanut plants under controlled rotary imaging. A total of 10,800 RGB images from 30 plants were used to compare representative implementations of incremental and global SfM-MVS pipelines in terms of geometric quality, phenotypic accuracy, and processing efficiency. At the 1° baseline, the tested global pipeline implementation reduced the root mean square reprojection error (RMSRE), point-density coefficient of variation (CV), vertical root mean square error (VRMSE), and the 95th percentile of the absolute point-cloud distance values (P95) by 15.05%, 14.08%, 39.87%, and 33.33%, respectively, and increased average phenotypic accuracy from 96.08% to 97.37%, compared with the tested incremental pipeline implementation. In contrast, the tested incremental implementation showed a lower voxel void ratio and shorter processing time. In both pipelines, increasing the angular interval reduced processing time but also reduced geometric stability, internal voxel filling, and phenotypic accuracy. In the present dataset, angular intervals of 3°–5° provided a favourable balance between reconstruction accuracy and efficiency. Cropping reduced peripheral redundancy, whereas cropping combined with background removal produced the best overall results, with the lowest reprojection error and the highest phenotypic accuracy. These results provide practical guidance for selecting reconstruction pipeline, viewpoint configuration, and preprocessing strategy in close-range indoor 3D phenotyping of peanut plants and crops with similar canopy architectures.

Plant phenotyping relevance

落花生の3D表現型取得について、SfM-MVSパイプライン、視点間隔、画像前処理を比較・検証しており、フェノタイピング手法が研究の中心である。

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