Direct processing of compressed SIFT feature vectors

Shmuel T. Klein, Dana Shapira

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


The problem of compressing a large collection of feature vectors so that object identification can further be processed on the compressed form of the features is investigated. The idea is to perform matching against a query image in the compressed form of the feature descriptor vectors retaining the metric. Specifically, we concentrate on SIFT (Scale Invariant Feature Transform), a known object detection method. Given two SIFT feature vectors, we suggest achieving our goal to compress them using a lossless encoding for which the pair wise matching can be done directly on the compressed files, by means of a Fibonacci code.

Original languageEnglish
Title of host publicationProceedings - DCC 2014
Subtitle of host publication2014 Data Compression Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages1
ISBN (Print)9781479938827
StatePublished - 2014
Externally publishedYes
Event2014 Data Compression Conference, DCC 2014 - Snowbird, UT, United States
Duration: 26 Mar 201428 Mar 2014

Publication series

NameData Compression Conference Proceedings
ISSN (Print)1068-0314


Conference2014 Data Compression Conference, DCC 2014
Country/TerritoryUnited States
CitySnowbird, UT


  • Compressed matching
  • Fibinacci codes
  • SIFT feature transform


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