Browsing by Author "Liu, Yang"

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    LiDAR Operation and Digital Modeling Visualization to Communicate Stormwater Management at Green Spaces in Developing Regions
    (The Eurographics Association, 2022) Lin, Chien-Yu; Ackerman, Aidan; Johnston, Douglas; Tian, Guohang; Liu, Yang; Dutta, Soumya; Feige, Kathrin; Rink, Karsten; Zeckzer, Dirk
    This research involves the application of LiDAR modifications from China Meteorological Data Service Centre (CMDC) along with landscape digital modeling visualization tools to explore future climate change adaptation, potential landscape performance and strategic management at the Green Expo Park in Zhengzhou, China. In terms of yearly and numerical reports of weather conditions by CMDC, patterns of runoff distribution and detentions are highly correlated with leaf area index (LAI) and associated factors such as ground materials and physical characteristic. This observation is valuable as environmental inspection for stormwater management at green spaces in developing regions and further understanding of collaboration for landscape architects, urban designers, urban planners, stakeholders and government agencies. Using a combination of a Li- DAR360 along with terrain 3D modeling and parametric plugin software, we visualized several surface flow scenarios which were used to potentially inform land of recreation, green spaces and water quality management. Data collected from a LiBackpack 50 instrument was selected for initial reference and processed in LiDAR360, after which point the data was exported for 3D modeling. Parametric plugins were used to develop data supported computational simulation in order to visualize runoff dispersal and aggregation that occurred as a result of various site conditions. These visualizations, developed from LiDAR to digital modeling using parametric digital tools, allowed data-driven exploration of stormwater management and climate change.
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    Temporally Sliced Photon Primitives for Time-of-flight Rendering
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Liu, Yang; Jiao, Shaojie; Jarosz, Wojciech; Ghosh, Abhijeet; Wei, Li-Yi
    We derive a class of new Monte Carlo estimators for volumetric time-of-flight rendering, generalizing prior work on transient photon points and beams. Conceptually, our method starts with any steady-state photon primitive – like a photon plane, parallelepiped, or parallelotope – and slices it with a temporal wavefront, producing a primitive of one dimension lower. We show how different unbiased temporally sliced primitives arise by analytically integrating any four dimensions within a novel extended spatio-temporal path space formulation. The differences between these estimators reduce to the determinant of a 4×4 Jacobian matrix, with columns dictated by the chosen dimensions. We then show how to combine the relative strengths of different sliced primitives using multiple importance sampling. Finally, we implement several of the new estimators enabled by our theory and compare them to each other as well as previous techniques.