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Dynamic Quantization: Two Adaptive Data Structures for Multidimensional Spaces
March 1984 (vol. 6 no. 3)
pp. 266-280
ASCII Text
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Joseph O'Rourke, Kenneth R. Sloan, "Dynamic Quantization: Two Adaptive Data Structures for Multidimensional Spaces," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 6, no. 3, pp. 266-280, March, 1984.
 
 
BibTex
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@article{ 10.1109/TPAMI.1984.4767519,
author = {Joseph O'Rourke and Kenneth R. Sloan},
title = {Dynamic Quantization: Two Adaptive Data Structures for Multidimensional Spaces},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {6},
number = {3},
issn = {0162-8828},
year = {1984},
pages = {266-280},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.1984.4767519},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Dynamic Quantization: Two Adaptive Data Structures for Multidimensional Spaces
IS - 3
SN - 0162-8828
SP266
EP280
EPD - 266-280
A1 - Joseph O'Rourke,
A1 - Kenneth R. Sloan,
PY - 1984
VL - 6
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Joseph O'Rourke, Department of Electrical Engineering and Computer Science, The Johns Hopkins University, Baltimore, MD 21218.
Kenneth R. Sloan, Architecture Machine Group, Massachusetts Institute of Technology, Cambridge, MA 02139.
Two new data structures are defined for use in multidimensional histogramming. Their purpose is to cover a parameter space with a limited number of histogram bins so that fine precision is maintained where it is needed. The original motivation for these data structures was to implement Hough-like transforms in high-dimensional parameter spaces. The two data structures share the ability to adapt to distributions that change with time.
Citation:
Joseph O'Rourke, Kenneth R. Sloan, "Dynamic Quantization: Two Adaptive Data Structures for Multidimensional Spaces," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 6, no. 3, pp. 266-280, March 1984, doi:10.1109/TPAMI.1984.4767519
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