2results about How to "Accurate depth information" patented technology

This invention discloses a method for constructing a realistic depth estimation training dataset based on a 3D mesh and 3D Gaussian splashing, relating to the field of UAV aerial surveying technology. The method involves acquiring aerial image sequences using a visible light camera mounted on a UAV platform, and filtering and preprocessing the image quality; generating a dense point cloud and a 3D mesh; training and generating a 3DGS model based on camera pose and image sequences consistent with the 3D mesh; unifying the 3D mesh, camera pose, and 3DGS model to the same world coordinate system; and using Z-buffer rasterization to output pixel-by-pixel depth and validity masks; generating RGB images of the corresponding viewpoint in the 3DGS renderer; and encapsulating the dataset according to a recommended data organization structure. This invention can accurately generate realistic RGB and geometrically accurate depth, with strict pixel alignment between the RGB images and depth maps, adapting to the needs of real-world application scenarios such as UAV aerial surveying and actual terrain mapping.

The invention provides a non-vision-field imaging method and device based on quasi-Fresnel transformation, and belongs to the technical field of optical non-vision-field imaging. The method comprises the following steps: collecting photon echo data when non-vision-field imaging is carried out on a non-vision-field target as a detection signal; calculating a convolution size parameter of the detection signal based on quasi-Fresnel transform; calculating a two-dimensional complex representation of the detection signal based on the convolution size parameter; calculating a two-dimensional complex representation of the non-view target based on the two-dimensional complex representation of the detection signal; and calculating reflectivity and depth information of the non-vision target based on the two-dimensional complex representation of the non-vision target so as to realize imaging of the non-vision target. According to the method, the two-dimensional features of the surface of the non-vision-field target are fully utilized, the non-vision-field target can be accurately and efficiently reconstructed, and the method has the advantages of being high in calculation speed, small in used memory, low in data dependence and accurate in imaging and positioning.