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casa 15(4): e4

Research Article

Human Object Detection based on Context Awareness in the Surroundings

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  • @ARTICLE{10.4108/eai.4-8-2015.150043,
        author={Nguyen  Thanh Binh},
        title={Human Object Detection based on Context Awareness in the Surroundings},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
        volume={2},
        number={4},
        publisher={ICST},
        journal_a={CASA},
        year={2015},
        month={8},
        keywords={Human Object Detection, Curvelet Transform, Support Vector Machine},
        doi={10.4108/eai.4-8-2015.150043}
    }
    
  • Nguyen Thanh Binh
    Year: 2015
    Human Object Detection based on Context Awareness in the Surroundings
    CASA
    ICST
    DOI: 10.4108/eai.4-8-2015.150043
Nguyen Thanh Binh1,*
  • 1: Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology, Vietnam
*Contact email: ntbinh@hcmut.edu.vn

Abstract

Surveillance system has been applied in providing public security for many complex places like railway stations, bus stops, etc. In most cases, human object detection is an important task in surveillance system. In the case that human objects are occlusion or outdoor environment, human objects detection is a challenging problem. In this paper, we propose a method to implement for human object detection based on context awareness in new wavelet generation domain in outdoor environment. We use curvelet transform based on context awareness combined with support vector machines as a classifier for human detection. The proposed method was tested on a standard dataset like PEST2001 dataset. For demonstrating the superiority of the proposed method, we have compared the results with the other recent methods available in literature.

Keywords
Human Object Detection, Curvelet Transform, Support Vector Machine
Received
2015-06-01
Accepted
2015-07-03
Published
2015-08-04
Publisher
ICST
http://dx.doi.org/10.4108/eai.4-8-2015.150043

Copyright © 􀀕􀀓􀀔􀀘 N.T. Binh, licensed to ICST. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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