Research map / Learning theory and algorithms / Matrix and tensor methods
Message Passing Least Squares Framework and its Application to Rotation Synchronization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use MPLS instead of the tested alternatives | rotation synchronization · Photo Tourism datasets | mean error (degrees) | Mixed |
| Use MPLS instead of IRLS-GM | rotation synchronization · Gendarmenmarkt | mean error (degrees): 39.24 -> 44.94 | Hurt |
| Use MPLS instead of CEMP+MST | rotation synchronization · Piazza Del Popolo | mean error (degrees): 3.44 -> 3.73 | Hurt |
| Use MPLS instead of CEMP+MST | rotation synchronization · Piccadilly | mean error (degrees): 4.66 -> 3.93 | Helped |
| Use MPLS instead of CEMP+MST | rotation synchronization · Tower of London | mean error (degrees): 2.84 -> 3.16 | Hurt |
| Use CEMP+MST rather than the iterative alternatives | rotation synchronization · Photo Tourism datasets | runtime | Helped |
| Use MPLS rather than IRLS methods | rotation synchronization · uniform synthetic corruption | mean error | Helped |
| Use MPLS rather than the other tested methods | rotation synchronization · self-consistent synthetic corruption | mean error | Helped |
| Initialize weights and update them using corruption estimates from CEMP, then reweight least squares | MPLS · rotation synchronization under corruption and noise | mean error | Helped |
| Truncate the reweighting function and decrease the truncation threshold across iterations | MPLS · rotation synchronization under noise and outliers | mean error | Helped |
| Initialize rotations by propagating measurements along a CEMP-weighted minimum spanning tree | MPLS-SO(3) · rotation synchronization | mean error | Mixed |
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