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Research map / 3D vision / Depth and stereo

HSfM: Hybrid Structure-from-Motion

CVPR 2017 · 3D vision › Depth and stereo · approach: Camera model and calibration for SfM · 155 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use hybrid global rotation averaging and incremental camera-center estimationHSfM · Trafalgarreconstructed cameras: 4945 -> 4966Helped
Use hybrid global rotation averaging and incremental camera-center estimationHSfM · Trafalgarmedian position error (m): 3.6 -> 2.6Helped
Use hybrid global rotation averaging and incremental camera-center estimationHSfM · Trafalgarmean position error (m): 8.6 -> 7.2Helped
Use hybrid global rotation averaging and incremental camera-center estimationHSfM · Piccadillyreconstructed cameras: 2276 -> 2279Helped
Use hybrid global rotation averaging and incremental camera-center estimationHSfM · Piccadillymedian position error (m): 0.4 -> 0.7Hurt
Use hybrid global rotation averaging and incremental camera-center estimationHSfM · Piccadillymean position error (m): 2.2 -> 2.0Helped
Use hybrid global rotation averaging and incremental camera-center estimationHSfM · Piccadillytotal runtime: 44369 -> 3293Helped
Use community-based rotation averaging instead of treating all cameras as one community (ablation)HSfM rotation estimation · Gendarmenmarktmedian rotation error (degrees): 40.6 -> 9.8Helped
Use community-based rotation averaging instead of treating all cameras as one community (ablation)HSfM rotation estimation · Gendarmenmarktmean rotation error (degrees): 54.9 -> 15.9Helped
Use hybrid HSfM rather than BundlerQuad reconstruction · Quadmedian position accuracy (m): 1.01m -> 1.03mNo clear effect

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