3D Computer Vision Engineer
- Джерело:
- djinni.co
Що робити
- Build a robust scan0 -> scan1 registration pipeline that aligns mostly-static structure while remaining insensitive to moved furniture and other transient objects.
- Handle partial overlap, occlusion, missing observations, drift, and scale differences between scans.
- Build temporal change detection that distinguishes:
- object removed / added,
- object moved,
Що очікуємо
- Strong background in 3D computer vision and geometric perception: point clouds, meshes, depth maps, coordinate transforms, registration, visibility/occlusion reasoning, and spatial change detection.
- Hands-on experience with real RGB-D / LiDAR / depth-sensor data. You should have dealt with noisy depth, incomplete scans, moving objects, partial overlap, and sensor/calibration errors.
- Strong understanding of 3D registration, including ICP variants, robust/global registration, geometric descriptors, RANSAC/TEASER++-style approaches, and failure detection.
- Experience solving multi-session or temporal mapping problems: comparing the same physical environment captured at different times.
- Familiarity with SLAM / visual-inertial odometry. You should understand accumulated drift, scale error, loop closure, and how errors in scan generation propagate downstream.
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