Alcantara Dan, Carmichael Owen, Delson Eric, Harcourt-Smith Will, Sterner Kirsten, Frost Stephen, Dutton Rebecca, Thompson Paul, Aizenstein Howard, Lopez Oscar, Becker James, Amenta Nina
Computer Science, University of California, Davis, USA.
Inf Process Med Imaging. 2007;20:519-31. doi: 10.1007/978-3-540-73273-0_43.
We introduce Localized Components Analysis (LoCA) for describing surface shape variation in an ensemble of biomedical objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for localized components and allows a flexible trade-off between localized and concise representations. Experiments comparing LoCA to a variety of competing shape representation methods on 2D and 3D shape ensembles establish the superior ability of LoCA to modulate the locality-conciseness tradeoff and generate shape components corresponding to intuitive modes of shape variation. Our formulation of locality in terms of compatibility between pairs of surface points is shown to be flexible enough to enable spatially-localized shape descriptions with attractive higher-order properties such as spatial symmetry.
我们引入了局部成分分析（LoCA），用于使用空间局部形状成分的线性子空间来描述生物医学对象集合中的表面形状变化。与早期方法不同，LoCA针对局部成分进行了显式优化，并允许在局部表示和简洁表示之间进行灵活权衡。在二维和三维形状集合上，将LoCA与各种竞争形状表示方法进行比较的实验表明，LoCA在调节局部性 - 简洁性权衡以及生成与直观形状变化模式相对应的形状成分方面具有卓越能力。我们根据表面点对之间的兼容性来定义局部性，结果表明这种定义足够灵活，能够实现具有诸如空间对称性等吸引人的高阶特性的空间局部形状描述。
