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A Study on an Effective Feature Selection Method Using Hog-Family Feature for Human Detection

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F14%3A43886126" target="_blank" >RIV/44555601:13440/14:43886126 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.sersc.org/journals/IJMUE/vol9_no12_2014/19.pdf" target="_blank" >http://www.sersc.org/journals/IJMUE/vol9_no12_2014/19.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.14257/ijmue.2014.9.12.19" target="_blank" >10.14257/ijmue.2014.9.12.19</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Study on an Effective Feature Selection Method Using Hog-Family Feature for Human Detection

  • Original language description

    It is the important that Support Vector Machine (SVM) is the powerful learning machines and has been applied to varying task with generally acceptable performance. The SVM success for classification tasks in one domain is affected by features that it represents the instance of specific class. The representative and discriminative features that they are given, SVM learning is going to provide better generalization and consequently that we are able to obtain good classifier. In this paper, we define the problem of feature choices for tasks of human detections and measure the performance of each feature. And also we consider HOG-family feature to study an effective feature selection method. Finally we proposed the multi-scale HOG as a NEW family member inthis feature group. In addition we also combine SVM with Principal Component Analysis (PCA) to reduce dimension of features and enhance the evaluation speed while retaining most of discriminative feature vectors.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    International Journal of Multimedia and Ubiquitous Engineering

  • ISSN

    1975-0080

  • e-ISSN

  • Volume of the periodical

    9

  • Issue of the periodical within the volume

    12

  • Country of publishing house

    KR - KOREA, REPUBLIC OF

  • Number of pages

    9

  • Pages from-to

    203-212

  • UT code for WoS article

  • EID of the result in the Scopus database