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Information Journal Paper

Title

A NOVEL DESCRIPTOR FOR PEDESTRIAN DETECTION IN VIDEO SEQUENCES

Pages

  1-8

Abstract

 This paper presents a novel TEXTURE-Edge Descriptor, TED, for background modeling and PEDESTRIAN DETECTION in video sequences which models TEXTURE and EDGE information of each image block simultaneously. Each block is modeled as a group of adaptive TED histograms that are calculated for pixels of the block over a rectangular neighborhood. TED is an 8-bit binary code which is independent of the neighborhood size. Experimental results over real-world sequences from PETS database clearly show that TED outperforms LBP.

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    APA: Copy

    ARMANFARD, NARGES, KOMEILI, MAJID, & KABIR, EHSANOLLAH. (2010). A NOVEL DESCRIPTOR FOR PEDESTRIAN DETECTION IN VIDEO SEQUENCES. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH, 2(2), 1-8. SID. https://sid.ir/paper/315071/en

    Vancouver: Copy

    ARMANFARD NARGES, KOMEILI MAJID, KABIR EHSANOLLAH. A NOVEL DESCRIPTOR FOR PEDESTRIAN DETECTION IN VIDEO SEQUENCES. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH[Internet]. 2010;2(2):1-8. Available from: https://sid.ir/paper/315071/en

    IEEE: Copy

    NARGES ARMANFARD, MAJID KOMEILI, and EHSANOLLAH KABIR, “A NOVEL DESCRIPTOR FOR PEDESTRIAN DETECTION IN VIDEO SEQUENCES,” INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH, vol. 2, no. 2, pp. 1–8, 2010, [Online]. Available: https://sid.ir/paper/315071/en

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