Built the indoor large-scene reconstruction system behind station-scanned spaces such as Realsee VR house tours, museums, and large venue digitization.

• Designed the full tiled parallel algorithm framework so reconstruction, mesh processing, texturing, simplification, and LOD generation can run beyond single-machine memory limits.
• Implemented topology-consistent block mesh merging, robust hole filling, irregular multi-floor segmentation, automatic ceiling hiding, semi-global color balancing, textured simplification, LOD strategy, and cloud Docker deployment.

Tech: C++, point clouds, mesh reconstruction, topology repair, texture optimization, LOD, Docker

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Developed a direct colorization pipeline for large sparse point clouds, mapping calibrated multi-view images onto LiDAR geometry while controlling visibility, view selection, and color seams.

• Built a block-based voxel visibility framework that uses neighboring blocks as occlusion context, Top-K candidate views, point-level projection checks, normal filtering, masks, and rolling-shutter row poses.
• Designed a distance-driven main-view selection strategy that forms spatially coherent view regions, then applies boundary multi-view consensus and sparse correction-field optimization for semi-global color harmonization.

Tech: C++, OpenVDB, point clouds, ray visibility, multi-view projection, Delaunay graph, conjugate gradient

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Built a production point-cloud filtering and geometric refinement pipeline for handheld laser scanning, turning raw keyframe clouds into clean global point clouds for downstream reconstruction.

• Designed a sparse-voxel, block-parallel processing framework with streaming partitioning, neighbor topology, boundary-safe ownership, and global result merging.
• Implemented time-aware dynamic-object removal, sub-voxel centroiding, robust normal orientation, anisotropic bilateral filtering, MST normal propagation, planar density homogenization, and sparse outlier cleanup.

Tech: C++, OpenVDB, handheld LiDAR, ray traversal, normal estimation, bilateral filtering, Poisson-disk sampling

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Designed a calibration workflow for station-based scanning and mobile handheld laser scanners, focusing on practical error sources and the path from diagnosis to validation.

• Formulated the main calibration problems: coupled sensor and mechanical errors, degraded planar geometry, repeatability risks, and camera-to-LiDAR alignment in production data capture.
• Used simulation to analyze error distributions, designed optimization and validation schemes, and added a high-precision calibration-field workflow that completes joint camera-LiDAR extrinsic calibration from a single data capture.

Tech: LiDAR calibration, camera-LiDAR extrinsics, error simulation, nonlinear optimization, calibration-field design

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Designed a geometry pipeline that recovers room structure from a given indoor mesh and reconstructs a regularized structural mesh.

• Built the full framework from scratch: space partitioning into a cell complex, visibility-based inside/outside reasoning, and graph-cut optimization.
• Independently implemented the complex cell-complex geometry algorithms, room partitioning, door recognition, and structure reconstruction modules.

Tech: C++, mesh processing, cell complex, visibility, graph cut, structural reconstruction

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Refined monocular depth estimation outputs from panoramic imagery into more stable point-cloud and mesh geometry for downstream reconstruction pipelines.

• Added pose consistency checks, outlier filtering, point-cloud fusion, and mesh cleanup.
• Bridged learned monocular depth predictions with production geometry quality requirements.

Tech: monocular depth estimation, pose BA, point-cloud fusion, mesh cleanup

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Designed an automatic DXF/DWG parser to convert non-standard manually drawn CAD floorplans into a unified structured floorplan representation.

• Handled inconsistent layers, drawing styles, line types, units, blocks, and geometry conventions across legacy CAD files.
• Independently designed and implemented algorithms for layer parsing, inside/outside classification, room partitioning, door/window recognition, door block recognition, furniture filtering, and floorplan data generation.

Tech: DXF/DWG, computational geometry, triangulation, region graph, door/window recognition, floorplan JSON

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Developed panorama preprocessing modules for gravity alignment and Manhattan direction estimation before reconstruction and spatial understanding.

• Implemented cube projection, spherical line reasoning, RANSAC, vanishing-point voting, and fast Manhattan scoring.
• Packaged geometric priors as reusable preprocessing steps for panorama-based workflows.

Tech: equirectangular panoramas, spherical LUT, vanishing points, gravity rectification, RANSAC

Gravity rectificationVanishing points

Built an automated building reconstruction pipeline from airborne LiDAR point clouds, turning classified building observations into vectorized 3D models with reconstructed roof structure.

• Segmented roof planes from building point clouds and defined custom topological relationships to describe complex roof assemblies.
• Reconstructed roof geometry under planar constraints and generated complete building vector models with optional aerial-image texture mapping.

Tech: airborne LiDAR, point-cloud classification, roof segmentation, topology modeling, vector reconstruction, texture mapping

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