Abstract: The present invention provides a method for repairing incomplete 3D depth image using 2D image information. The method includes the following steps: obtaining 2D image information and 3D depth image information; dividing 2D image information into 2D reconstruction blocks and 2D reconstruction boundaries, and corresponding to 3D reconstruction of blocks and 3D reconstruction boundaries; analyzing each 3D reconstruction block, partitioning into residual-surface blocks and repaired blocks; and proceeding at least one 3D image reconstruction, which extends with the initial depth value of the 3D depth image of each of the residual-surface block and covers all the corresponding repaired block to form a repair block and to achieve the purpose of repairing incomplete 3D depth images using 2D image information.

Abstract: The present invention provides a method for repairing incomplete 3D depth image using 2D image information. The method includes the following steps: obtaining 2D image information and 3D depth image information; dividing 2D image information into 2D reconstruction blocks and 2D reconstruction boundaries, and corresponding to 3D reconstruction of blocks and 3D reconstruction boundaries; analyzing each 3D reconstruction block, partitioning into residual-surface blocks and repaired blocks; and proceeding at least one 3D image reconstruction, which extends with the initial depth value of the 3D depth image of each of the residual-surface block and covers all the corresponding repaired block to form a repair block and to achieve the purpose of repairing incomplete 3D depth images using 2D image information.

Abstract: A method and system for target detecting, editing and rebuilding by 3D image is provided, which comprises an inputting and picking unit, a training and detecting unit, a displaying and editing unit and a rebuilding unit. The inputting and picking unit receives a digital image and a LiDAR data and picks up a first parameter to form a 3D image. The training and detecting unit selects a target, picks up a second parameter therefrom, calculates the second parameter to generate a threshold and detects the target areas in the 3D image according to the threshold. The displaying and editing unit sets a quick selecting tool according to the threshold and edits the detecting result. The rebuilding unit sets a buffer area surrounding the target, picks up a third parameter therefrom and calculates the original shape of the target by the Surface Fitting method according to the third parameter.

Abstract: A method and system for target detecting, editing and rebuilding by 3D image is provided, which comprises an inputting and picking unit, a training and detecting unit, a displaying and editing unit and a rebuilding unit. The inputting and picking unit receives a digital image and a LiDAR data and picks up a first parameter to form a 3D image. The training and detecting unit selects a target, picks up a second parameter therefrom, calculates the second parameter to generate a threshold and detects the target areas in the 3D image according to the threshold. The displaying and editing unit sets a quick selecting tool according to the threshold and edits the detecting result. The rebuilding unit sets a buffer area surrounding the target, picks up a third parameter therefrom and calculates the original shape of the target by the Surface Fitting method according to the third parameter.