Active Terahertz Imaging Dataset for Concealed Object Detection

-Project Page & Dataset

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Introduction

Concealed object detection in Terahertz imaging is an urgent need for public security and counter-terrorism. In this paper, we provide a public dataset for evaluating multi-object detection algorithms in active Terahertz imaging resolution 5 mm by 5 mm. To the best of our knowledge, this is the first public Terahertz imaging dataset prepared to evaluate object detection algorithms. Object detection on this dataset is much more difficult than on those standard public object detection datasets due to its inferior imaging quality. Facing the problem of imbalanced samples in object detection and hard training samples, we evaluate four popular detectors: YOLOv3, YOLOv4, FRCN-OHEM, and RetinaNet on this dataset. Experimental results indicate that the RetinaNet achieves the highest mAP. In addition, we demonstrate that hiding objects in different parts of the human body affect detection accuracy. The dataset will be available online.

Dataset

Object classes and quantity of the dataset.

Class	GA	KK	SS	MD	CK	WB	KC	CP	CL	LW	UN	In total
Item	Gun	Kitchen Knife	Scissors	Metal Dagger	Ceramic Knife	Water Bottle	Key Chain	Cell Phone	Cigarette Lighter	Leather Wallet	Unknown	--
Quantity	116	100	96	64	129	107	78	129	163	78	289	1349

Sample display for each category. The bottom row shows a zoomed-in view of the object.

Sample display for diversification.

Dataset structure:

/THZ_dataset_det_VOC
    /Annotations
        /D_N_F1_CK_F_LA_WB_F_S_back_0907140917.xml
        /D_N_F1_CK_F_LA_WB_F_S_front_0907140917.xml
        /D_N_F1_CL_V_LA_LW_V_RA_back_0907141138.xml
        /...
        /T_P_M6_MD_F_LL_CK_F_C_WB_F_RT_front_0906154134.xml
    /JPEGImages
        /D_N_F1_CK_F_LA_WB_F_S_back_0907140917.jpg
        /D_N_F1_CK_F_LA_WB_F_S_front_0907140917.jpg
        /D_N_F1_CL_V_LA_LW_V_RA_back_0907141138.jpg
        /...
        /T_P_M6_MD_F_LL_CK_F_C_WB_F_RT_front_0906154134.jpg

Download links:

• Google drive
• Baidu drive(Extraction code: x3od)
• NUAA drive

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If you find this dataset useful in your research, please consider citing:

@misc{liang2021active,
      title={Active Terahertz Imaging Dataset for Concealed Object Detection}, 
      author={Dong Liang and Fei Xue and Ling Li},
      year={2021},
      eprint={2105.03677},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}