Face detection through compact classifier using adaptive look-up-table

Yuya Hanai, Tadahiro Kuroda

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

    1 Citation (Scopus)

    Abstract

    Face detection has been well studied in terms of accuracy and speed. However, required memory size reduction is still poorly studied, which is becoming a critical issue as platforms for face detection go tiny. In this paper, we propose a novel compact weak classifier using Adaptive Look-Up-Table (ALUT) for face detection on resource-constrained devices such as wearable sensor nodes. ALUT gives good approximation of log-likelihood [3] with fewer data, thus enabling the drastic reduction of classifier data size, keeping high accuracy and low computation cost. To generate an optimal ALUT, a new cost function called Weighted Sum of Absolute Difference (WSAD) is also proposed for further improvement. In our experiment, the classifier data size is reduced by 43% and the computation cost is reduced by 15% with same accuracy, compared to a conventional fixed LUT classifier.

    Original languageEnglish
    Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
    PublisherIEEE Computer Society
    Pages1225-1228
    Number of pages4
    ISBN (Print)9781424456543
    DOIs
    Publication statusPublished - 2009 Jan 1
    Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
    Duration: 2009 Nov 72009 Nov 10

    Publication series

    NameProceedings - International Conference on Image Processing, ICIP
    ISSN (Print)1522-4880

    Other

    Other2009 IEEE International Conference on Image Processing, ICIP 2009
    Country/TerritoryEgypt
    CityCairo
    Period09/11/709/11/10

    Keywords

    • Dynamic programming
    • Object detection
    • Signal partitioning
    • Wearable computing

    ASJC Scopus subject areas

    • Software
    • Computer Vision and Pattern Recognition
    • Signal Processing

    Fingerprint

    Dive into the research topics of 'Face detection through compact classifier using adaptive look-up-table'. Together they form a unique fingerprint.

    Cite this