pub enum Algorithm {
KabschUmeyama,
RobustArun,
}Expand description
Algorithm selection for point cloud alignment.
This enum specifies which algorithm to use when aligning two sets of 3D points. Different algorithms have different robustness characteristics and computational requirements.
Variants§
KabschUmeyama
The Kabsch-Umeyama algorithm for point set alignment.
This is a classic algorithm that finds the optimal similarity transformation (scale, rotation, translation) between two point sets. It’s mathematically elegant but can be sensitive to outliers.
RobustArun
A robustly-scaled variant of the Arun, Huang, and Blostein algorithm.
This algorithm provides more robust scaling estimation compared to Kabsch-Umeyama, making it more suitable for real-world data that may contain noise or outliers.
Auto Trait Implementations§
impl Freeze for Algorithm
impl RefUnwindSafe for Algorithm
impl Send for Algorithm
impl Sync for Algorithm
impl Unpin for Algorithm
impl UnsafeUnpin for Algorithm
impl UnwindSafe for Algorithm
Blanket Implementations§
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T: ?Sized,
impl<T> BorrowMut<T> for Twhere
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Converts
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if into_left is true.
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if into_left(&self) returns true.
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The inverse inclusion map: attempts to construct
self from the equivalent element of its
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fn from_subset(element: &SS) -> SP
The inclusion map: converts
self to the equivalent element of its superset.