502 research outputs found
Fast Exact Search in Hamming Space with Multi-Index Hashing
There is growing interest in representing image data and feature descriptors
using compact binary codes for fast near neighbor search. Although binary codes
are motivated by their use as direct indices (addresses) into a hash table,
codes longer than 32 bits are not being used as such, as it was thought to be
ineffective. We introduce a rigorous way to build multiple hash tables on
binary code substrings that enables exact k-nearest neighbor search in Hamming
space. The approach is storage efficient and straightforward to implement.
Theoretical analysis shows that the algorithm exhibits sub-linear run-time
behavior for uniformly distributed codes. Empirical results show dramatic
speedups over a linear scan baseline for datasets of up to one billion codes of
64, 128, or 256 bits
Building Proteins in a Day: Efficient 3D Molecular Reconstruction
Discovering the 3D atomic structure of molecules such as proteins and viruses
is a fundamental research problem in biology and medicine. Electron
Cryomicroscopy (Cryo-EM) is a promising vision-based technique for structure
estimation which attempts to reconstruct 3D structures from 2D images. This
paper addresses the challenging problem of 3D reconstruction from 2D Cryo-EM
images. A new framework for estimation is introduced which relies on modern
stochastic optimization techniques to scale to large datasets. We also
introduce a novel technique which reduces the cost of evaluating the objective
function during optimization by over five orders or magnitude. The net result
is an approach capable of estimating 3D molecular structure from large scale
datasets in about a day on a single workstation.Comment: To be presented at IEEE Conference on Computer Vision and Pattern
Recognition (CVPR) 201
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