Object Tracking Based on Spatial-polarization Aliasing for Infrared Polarization Video

doi:10.12382/bgxb.2023.0600

Abstract

Abstract:

The division-of-focal-plane (DoFP)-based Infrared polarization imager has a strong anti-interference against complex weather and infrared camouflage while having the advantages of small size, batter real-time and high accuracy as well. However, the polarization mosaic image obtained by the imager need to be demosaiced and the polarization parameters should be calculated, which are time-consuming and contains inevitable errors, thus limiting the application of the imager in real-time object tracking. To solve this problem, the correlation between the spatial and polarization field is studied, and an object tracking method based on the designed histograms of spatial-polarization mixture gradient (HSPMG) feature extraction method is proposed. A spatial gradient operator is designed to obtain the spatial information of an image based on the spatial correlation between the polarization channels, and a polarized gradient operator is designed based on the polarization pseudo-panchromatic image (PPPI) and the spatial correlation between the polarization channels. Then the HSPMG feature is constructed based on the spatial and polarization information. To implement tracking on the infrared polarization mosaic image based on the spatial-polarization aliasing information, the HSPMG feature is applied to the AutoTrack object tracking method. Experiences on the infrared polarization mosaic dataset demonstrate that the feature extraction method could enhance the accuracy and speed of object tracking result.

Key words: polarization image, feature extraction, object tracking, spatial-polarization mixture gradient

CLC Number:

TN219

QIAO Xinbo, ZHAO Yongqiang, ZHANG Jingcheng. Object Tracking Based on Spatial-polarization Aliasing for Infrared Polarization Video[J]. Acta Armamentarii, 2024, 45(9): 3274-3287.

Figures/Tables 12

References 42

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方法	原始马赛克图像			去马赛克强度图像			偏振、强度融合图像
方法	跟踪精度	成功率	帧率	跟踪精度	成功率	帧率	跟踪精度	成功率	帧率
HSPMG	0.9428	0.8435	36.64
HOG	0.8990	0.7998	26.18	0.944	0.8425	1.42	0.8363	0.7032	1.56
HSOG	0.8069	0.6854	1.89	0.7925	0.6833	0.74	0.5560	0.4360	0.79
SSHMG	0.8784	0.7707	15.43	0.9102	0.8022	1.54	0.7560	0.6112	1.51
SIFT	0.8910	0.7839	0.37	0.9162	0.8132	0.25	0.7376	0.6016	0.19
LBP	0.3810	0.2750	0.64	0.2137	0.1691	0.38	0.2849	0.2108	0.40
Grayscale	0.7629	0.6529	200.01	0.7668	0.6607	1.15	0.5815	0.4543	1.22
HOG+Grayscale	0.8970	0.7973	39.58	0.9289	0.8232	1.12	0.7101	0.6001	0.95

方法	原始马赛克图像			去马赛克强度图像			偏振、强度融合图像
方法	跟踪精度	成功率	帧率	跟踪精度	成功率	帧率	跟踪精度	成功率	帧率
HSPMG	0.9428	0.8435	36.64
HOG	0.8990	0.7998	26.18	0.944	0.8425	1.42	0.8363	0.7032	1.56
HSOG	0.8069	0.6854	1.89	0.7925	0.6833	0.74	0.5560	0.4360	0.79
SSHMG	0.8784	0.7707	15.43	0.9102	0.8022	1.54	0.7560	0.6112	1.51
SIFT	0.8910	0.7839	0.37	0.9162	0.8132	0.25	0.7376	0.6016	0.19
LBP	0.3810	0.2750	0.64	0.2137	0.1691	0.38	0.2849	0.2108	0.40
Grayscale	0.7629	0.6529	200.01	0.7668	0.6607	1.15	0.5815	0.4543	1.22
HOG+Grayscale	0.8970	0.7973	39.58	0.9289	0.8232	1.12	0.7101	0.6001	0.95

参数	天气
参数	晴天	雨天	雾天	夜晚	强干扰	全部
跟踪精度	0.9633	0.9773	0.9754	0.9866	0.8383	0.9428
成功率	0.8825	0.8540	0.8319	0.8843	0.7686	0.8435
帧率	28.49	37.33	35.56	41.37	29.96	36.64

参数	天气
参数	晴天	雨天	雾天	夜晚	强干扰	全部
跟踪精度	0.9633	0.9773	0.9754	0.9866	0.8383	0.9428
成功率	0.8825	0.8540	0.8319	0.8843	0.7686	0.8435
帧率	28.49	37.33	35.56	41.37	29.96	36.64

方法	原始马赛克图像			去马赛克强度图像			偏振、强度融合图像
方法	跟踪精度	成功率	帧率	跟踪精度	成功率	帧率	跟踪精度	成功率	帧率
HSPMG	0.9428	0.8435	36.64
AutoTrack	0.8970	0.7973	39.58	0.9289	0.8232	1.12	0.7101	0.6001	0.95
ECO	0.9358	0.8172	22.72	0.9434	0.8280	1.33	0.5833	0.463	1.49
GFS-DCF	0.9036	0.7771	29.40	0.8745	0.7547	1.42	0.6331	0.511	1.39
GFS-DCF deep	0.7909	0.6572	3.82	0.8295	0.6979	0.99	0.7610	0.6156	1.55
ARCF	0.9221	0.8146	53.17	0.9300	0.8184	1.44	0.7979	0.6623	1.29
ASRCF	0.7840	0.6634	12.16	0.7912	0.6642	1.05	0.7137	0.5858	1.27
STRCF	0.9220	0.8036	46.96	0.9013	0.7884	1.40	0.7629	0.6199	1.54
STRCF deep	0.8457	0.7267	5.3687	0.8747	0.7449	1.10	0.7671	0.6264	1.26
CSR-DCF	0.9133	0.7142	15.41	0.8526	0.6596	1.40	0.7224	0.5579	1.38
BACF	0.8871	0.7791	61.14	0.9473	0.8349	1.62	0.8012	0.6636	1.20