Title of article :
TED: A texture-edge descriptor for pedestrian detection in video sequences
Author/Authors :
Armanfard، Narges نويسنده , , Narges and Komeili، نويسنده , , Majid and Kabir، نويسنده , , Ehsanollah، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Pages :
10
From page :
983
To page :
992
Abstract :
This paper presents a novel descriptor, TED, for pedestrian detection in video sequences. TED describes texture and edge information simultaneously. TED is a local descriptor because it is defined over a neighborhood. The size of the TED, independent of the neighborhood size defined over it, is 8 bits. TED is based on intensity difference, and so it is robust against illumination changes. We demonstrate TED performance in a block-based framework for pedestrian detection. Experimental results show the effectiveness of the proposed descriptor when applied in different outdoor and indoor environments.
Keywords :
pedestrian detection , Texture , EDGE , Block-based approach , Local Binary Pattern , background subtraction , Surveillance systems
Journal title :
PATTERN RECOGNITION
Serial Year :
2012
Journal title :
PATTERN RECOGNITION
Record number :
1734357
Link To Document :
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