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Open Access Publications from the University of California

Scholarly Works (4 results)

  • Article
  • Peer Reviewed
IDAV Publications (2009)
We demonstrate an efficient data-parallel algorithm for building large hash tables of millions of elements in real-time. We consider two parallel algorithms for the construction: a classical sparse perfect hashing approach, and cuckoo hashing, which packs elements densely by allowing an element to be stored in one of multiple possible locations. Our construction is a hybrid approach that uses both algorithms. We measure the construction time, access time, and memory usage of our implementations and demonstrate real-time performance on large datasets: for 5 million key-value pairs, we construct a hash table in 35.7 ms using 1.42 times as much memory as the input data itself, and we can access all the elements in that hash table in 15.3 ms. For comparison, sorting the same data requires 36.6 ms, but accessing all the elements via binary search requires 79.5 ms. Furthermore, we show how our hashing methods can be applied to two graphics applications: 3D surface intersection for moving data and geometric hashing for image matching.
    Cover page: Real-Time Parallel Hashing on the GPU
    • Article
    • Peer Reviewed
    UC Davis Previously Published Works (2009)

    Localized Components Analysis (LoCA) is a new method for describing surface shape variation in an ensemble of 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, and the formulation of locality is flexible enough to incorporate properties such as symmetry. This paper demonstrates that LoCA can provide intuitive presentations of shape differences associated with sex, disease state, and species in a broad range of biomedical specimens, including human brain regions and monkey crania.

      Cover page: Exploration of shape variation using localized components analysis.
      • Article
      • Peer Reviewed
      IDAV Publications (2005)
      We introduce a technique to visualize the gradual evolutionary change of the shapes of living things as a morph between known three-dimensional shapes. Given geometric computer models of anatomical shapes for some collection of specimens - here the skulls of the some of the extant members of a family of monkeys - an evolutionary tree for the group implies a hypothesis about the way in which the shape changed through time. We use a statistical method which expresses the value of some variable - in this case the shape - at an internal point in the tree as a weighted average of the values at the leaves. The framework of geometric morphometrics can then be used to define a shape-space, based on the correspondences of landmark points on the surfaces, within which these weighted averages can be realized as actual surfaces. Our software provides tools for performing and visualizing such an analysis in three dimensions. Beginning with laser range surfaces scans of skulls, we use our landmark editor to interactively place landmark points on the surface. We use these to compute a treemorph which smoothly interpolates the shapes across the tree. Each intermediate shape in the morph is a linear combination of all of the input surfaces. We create a surface model for an intermediate shape by warping all the input meshes towards the correct shape and then merging them together. Our merging procedure is novel. Given several similar surface meshes, we compute a weighted average between them by averaging their associated trivariate squared distance functions, and then extract the extremal surface which traces out the ''valleys'' along which the averaged function is nearly zero.
        Cover page: Evolutionary Morphing
        • Article
        • Peer Reviewed
        UC Davis Previously Published Works (2008)

        Hypertension is highly prevalent in elderly individuals and may be associated with cognitive decline, but the mechanisms by which hypertension may impact brain structure, and thereby modulate the time course of late-life cognitive performance, are not well understood. Therefore we used Localized Components Analysis, a novel computational method, to measure spatially-localized patterns of corpus callosum (CC) atrophy in 28 right-handed female subjects aged 75-79 years in the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik), a large-scale epidemiological study of aging. Localized callosal atrophy in the posterior midbody and splenium was significantly associated with systolic blood pressure in linear statistical models that controlled for age, while associations between blood pressure and anterior CC atrophy measures were not statistically significant. Additionally, overall measures of global CC atrophy were not significantly associated with blood pressure. The posterior CC may be differentially vulnerable to hypertension-associated atrophy, possibly due to its relatively tenuous vascularization.

          Cover page: Localized measures of callosal atrophy are associated with late-life hypertension: AGES-Reykjavik Study.
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