A Novel Descriptor for Pedestrian Detection in Video Sequences

Publish Year: 1389
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:

JR_ITRC-2-2_001

تاریخ نمایه سازی: 23 فروردین 1401

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 ۸-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.

Authors

Narges Armanfard

Dept. of Electrical and Computer Eng. Tarbiat Modarres University Tehran, Iran

Majid Komeili

Dept. of Electrical and Computer Eng. Tarbiat Modarres University Tehran, Iran

Ehsanollah Kabir

Dept. of Electrical and Computer Eng. Tarbiat Modarres University Tehran, Iran