Forward Index Compression for Instance Retrieval in an Augmented Reality Application

Qi Wang, Michal Siedlaczek, Yen Yu Chen, Michael Gormish, Torsten Suel

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Instance retrieval systems are widely used in applications such as robot navigation, medical diagnosis, and augmented reality. Blippar is a company that creates compelling augmented reality experiences or provides you with the tools to build your own. In this paper we focus on one of the company's augmented-reality applications, with which users are able to point their phone cameras at different objects in order to receive information about the objects in real time. In this paper, we provide what we believe to be the first study of forward index compression techniques for such instance retrieval systems. First, we perform an analysis of real-world data from a large-scale commercial instance retrieval system, run by Blippar focusing on augmented reality. Then we propose an entropy-based lossless compression strategy. Experiments show that our proposed Huffman-based approach outperforms a variety of other compression techniques, while also increasing overall system efficiency slightly.

    Original languageEnglish (US)
    Title of host publicationProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
    EditorsChaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1946-1952
    Number of pages7
    ISBN (Electronic)9781728108582
    DOIs
    StatePublished - Dec 2019
    Event2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States
    Duration: Dec 9 2019Dec 12 2019

    Publication series

    NameProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

    Conference

    Conference2019 IEEE International Conference on Big Data, Big Data 2019
    CountryUnited States
    CityLos Angeles
    Period12/9/1912/12/19

    Keywords

    • Augmented Reality
    • Index Compression
    • Instance Retrieval
    • Retrieval Efficiency

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Networks and Communications
    • Information Systems
    • Information Systems and Management

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