@techreport{oai:ipsj.ixsq.nii.ac.jp:00242256,
 author = {Ryo, Furukawa and Hiroshi, Kawasaki and Ryusuke, Sagawa and Ryo, Furukawa and Hiroshi, Kawasaki and Ryusuke, Sagawa},
 issue = {30},
 month = {Jan},
 note = {3D measurement for endoscopic systems has been largely demanded. One promising approach is to utilize active-stereo systems using a micro-sized pattern-projector attached to a head of a endoscope. Furthermore, a multi-frame integration is also desired to enlarge the reconstructed area. In this paper, we propose an incremental optimization technique of both the shape-field parameters and the positional parameters of the cameras and projectors. The method assumes that the input data is temporarily sequential images, i.e., endoscopic videos, and the relative positions between the camera and the projector may vary continuously. For solution, differential volume rendering algorithm conjunction with neural signed distance field (NeuralSDF) representation is proposed to simultaneously optimize the 3D scene and the camera/projector poses. Also, incremental optimization strategy where the optimized frames are gradually increased is proposed. In the experiment, the proposed method is evaluated by performing 3D reconstruction using both synthetic and real images, proving the effectiveness of our method., 3D measurement for endoscopic systems has been largely demanded. One promising approach is to utilize active-stereo systems using a micro-sized pattern-projector attached to a head of a endoscope. Furthermore, a multi-frame integration is also desired to enlarge the reconstructed area. In this paper, we propose an incremental optimization technique of both the shape-field parameters and the positional parameters of the cameras and projectors. The method assumes that the input data is temporarily sequential images, i.e., endoscopic videos, and the relative positions between the camera and the projector may vary continuously. For solution, differential volume rendering algorithm conjunction with neural signed distance field (NeuralSDF) representation is proposed to simultaneously optimize the 3D scene and the camera/projector poses. Also, incremental optimization strategy where the optimized frames are gradually increased is proposed. In the experiment, the proposed method is evaluated by performing 3D reconstruction using both synthetic and real images, proving the effectiveness of our method.},
 title = {Incremental shape integration with inter-frame shape consistency using Neural SDF for a 3D Endoscopic system},
 year = {2025}
}