@techreport{oai:ipsj.ixsq.nii.ac.jp:00231940,
 author = {髙橋, 響熙 and 上田, 樹 and 謝, 淳 and 北原, 格 and Hibiki, Takahashi and Itsuki, Ueda and Chun, Xie and Itaru, Kitahara},
 issue = {18},
 month = {Jan},
 note = {We propose a monocular Visual SLAM system based on NeDDF (Neural Density-Distance Field). In contrast to previous methods using point clouds or meshes, our approach has an advantage to reconstruct objects with indistinct boundaries, such as steam, smoke, dust, and similar phenomena. Our method utilizes NeDDF as a 3D shape representation and introduces a photometric error to account for the challenging smoke environment. This approach enables the reconstruction of indoor scenes featuring low-density objects using a monocular RGB camera. To evaluate the effectiveness of our proposed method, we conduct experiments using a simulated RGB dataset of an indoor scene with smoke., We propose a monocular Visual SLAM system based on NeDDF (Neural Density-Distance Field). In contrast to previous methods using point clouds or meshes, our approach has an advantage to reconstruct objects with indistinct boundaries, such as steam, smoke, dust, and similar phenomena. Our method utilizes NeDDF as a 3D shape representation and introduces a photometric error to account for the challenging smoke environment. This approach enables the reconstruction of indoor scenes featuring low-density objects using a monocular RGB camera. To evaluate the effectiveness of our proposed method, we conduct experiments using a simulated RGB dataset of an indoor scene with smoke.},
 title = {NeDDFを用いた煙霧環境に適用可能なニューラル場単眼Visual SLAM},
 year = {2024}
}