More Works from Our Lab

Paper Title 1

Brief description of the work and its main contribution.

Conference/Journal 2024
Paper Title 2

Brief description of the work and its main contribution.

Conference/Journal 2023
Paper Title 3

Brief description of the work and its main contribution.

Conference/Journal 2023

Neural 3D Reconstruction and Immersive VR Visualization of Row Crops Across Phenological Growth Stages

Shambhavi Joshi, Juan Di Salvo, Yanben Shen, Mozhgan Hadadi, Venkata Naresh Boddepalli, Talukder Jubery, Soumik Sarkar, Arti Singh, Baskar Ganapathysubramanian, Asheesh K. Singh, Adarsh Krishnamurthy
Iowa State University
Smart Agriculture Technology
Paper Supplementary Code arXiv
Pipeline

Real capture → NeRF / GSplat reconstruction → Unreal Engine visualization.

Abstract

Plant phenotyping in precision agriculture increasingly requires high-fidelity three-dimensional reconstruction and accessible visualization methods. This study presents an integrated pipeline combining Neural Radiance Fields (NeRF), 3D Gaussian Splatting (G-Splat), and Virtual Reality (VR) visualization for comprehensive plant analysis across developmental stages. We collected multi-view imagery of finger millet, proso millet, mungbean, and field pea under controlled greenhouse conditions, aligning data acquisition with standardized BBCH phenological scales. Camera pose estimation was performed using GLOMAP, followed by reconstruction via both Nerfacto and G-Splat implementations. Quantitative evaluation using PSNR, SSIM, and LPIPS metrics revealed complementary strengths of the two approaches: G-Splat achieved superior structural fidelity, while NeRF provided enhanced perceptual realism. Both reconstruction methods were successfully integrated into an immersive VR greenhouse environment deployed on Meta Quest headsets, maintaining consistently high framerates. This framework establishes a practical foundation for incorporating neural reconstruction and immersive technologies into agricultural phenotyping workflows, supporting both research applications and educational engagement.

3D Reconstruction Across Growth Stages

NeRF-based 3D point cloud reconstructions capturing the full growth cycle of Cereal plants, from early development to maturity. Each model represents a distinct growth stage, providing a consistent and detailed 3D view of plant structural and morphological evolution over time.

3D Reconstruction Across Growth Stages

NeRF-based 3D point cloud reconstructions capturing the full growth cycle of proso millet, from early development to maturity. Each model represents a distinct growth stage, providing a consistent and detailed 3D view of plant structural and morphological evolution over time.

Result

NeRF reconstructions for each plant species with corresponding BBCH labels shown beneath each reconstruction to indicate growth progression.

Greenhouse

Virtual greenhouse visualization showing reconstructed millet, mungbean, and pea plants with interactive growth-stage information panels. Each plant is paired with descriptive notecards displaying collection dates, growth stages, and visual references, providing an immersive environment for comparative analysis of plant development in 3D.

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BibTeX

@article{YourPaperKey2024,
  title={Your Paper Title Here},
  author={First Author and Second Author and Third Author},
  journal={Conference/Journal Name},
  year={2024},
  url={https://your-domain.com/your-project-page}
}