Abstract: Disclosed is a sewage pipe network hydraulic model building method based on three-dimensional geographic information. According to the method, physical corresponding relation between each manhole node of the sewage pipe network and surrounding buildings is obtained through the three-dimensional geographic information, the population of the sewage pipe network is estimated as prior information according to the corresponding relation, an optimization algorithm is used to determine the total influent time series of all manhole nodes in a region based on the population proportion, and flow fluctuation coefficient for each manhole node is optimized and calculated, such that the influent time series of each manhole node is determined, and the sewage pipe network hydraulic model is built accurately. The present disclosure further provides a method that uses the population data to replace the pipe length/catchment area data as the prior information for sewage pipe network flow check.

Abstract: An adaptive depth sensing system (ADSS) illuminates a scene with a pattern that is constructed based on an analysis of at least one prior-generated depth map. In one implementation, the pattern is a composite pattern that includes two or more component patterns associated with different depth regions in the depth map. The composite pattern may also include different illumination intensities associated with the different depth regions. By using this composite pattern, the ADSS can illuminate different objects in a scene with different component patterns and different illumination intensities, where those objects are located at different depths in the scene. This process, in turn, can reduce the occurrence of defocus blur, underexposure, and overexposure in the image information.

Abstract: Multiple images of a scene are captured while a phase-shifted fringe embedded with a secondary pattern is projected onto the scene. A wrapped phase map is generated based on the captured images, and a continuous region mask is determined to segment the wrapped phase map into multiple continuous regions. A period disparity of the fringe is determined for each region based at least in part on the embedded secondary pattern, and the regional period disparities are applied to a spatially unwrapped phase map to produce an absolute phase map and finally a depth map.

Abstract: An adaptive depth sensing system (ADSS) illuminates a scene with a pattern that is constructed based on an analysis of at least one prior-generated depth map. In one implementation, the pattern is a composite pattern that includes two or more component patterns associated with different depth regions in the depth map. The composite pattern may also include different illumination intensities associated with the different depth regions. By using this composite pattern, the ADSS can illuminate different objects in a scene with different component patterns and different illumination intensities, where those objects are located at different depths in the scene. This process, in turn, can reduce the occurrence of defocus blur, underexposure, and overexposure in the image information.

Abstract: Multiple images of a scene are captured while a phase-shifted fringe embedded with a secondary pattern is projected onto the scene. A wrapped phase map is generated based on the captured images, and a continuous region mask is determined to segment the wrapped phase map into multiple continuous regions. A period disparity of the fringe is determined for each region based at least in part on the embedded secondary pattern, and the regional period disparities are applied to a spatially unwrapped phase map to produce an absolute phase map and finally a depth map.

Abstract: An adaptive depth sensing system (ADSS) illuminates a scene with a pattern that is constructed based on an analysis of at least one prior-generated depth map. In one implementation, the pattern is a composite pattern that includes two or more component patterns associated with different depth regions in the depth map. The composite pattern may also include different illumination intensities associated with the different depth regions. By using this composite pattern, the ADSS can illuminate different objects in a scene with different component patterns and different illumination intensities, where those objects are located at different depths in the scene. This process, in turn, can reduce the occurrence of defocus blur, underexposure, and overexposure in the image information.

Abstract: An adaptive depth sensing system (ADSS) illuminates a scene with a pattern that is constructed based on an analysis of at least one prior-generated depth map. In one implementation, the pattern is a composite pattern that includes two or more component patterns associated with different depth regions in the depth map. The composite pattern may also include different illumination intensities associated with the different depth regions. By using this composite pattern, the ADSS can illuminate different objects in a scene with different component patterns and different illumination intensities, where those objects are located at different depths in the scene. This process, in turn, can reduce the occurrence of defocus blur, underexposure, and overexposure in the image information.