@inproceedings{96815624d8fb44ceba6b1b71acdf4836,
title = "Polarization Gradient Histogram for Object Tracking in Infrared Polarization Imaging: A Feature Extraction Method for Polarization Mosaic Image",
abstract = "Infrared polarization feature improves the performance of anti-interference for object detection. Division-of-focal-plane polarization imagers (DPIs) make it possible for real-time object tracking in infrared polarization imaging. Output of DPIs is polarization mosaic image. Traditional processing way is combined by demosaicing and then computing polarization parameters for object detection and tracking, which is time consuming and subjected to demosaicing error. This paper proposes a histogram of infrared polarization mosaic gradient (HIPMG) for feature extraction in infrared polarization image. In our proposed algorithm, Polarization and Spatial Correlation Matrixes (PCM and SCM) are designed to obtain spatial and polarization correlation of the object. Based on PCM and SCM, two Polarization Filter Matrixes (PFM) are proposed to obtain spatial-polarization gradient maps (SPGMs). Then a HIPMG descriptor is designed from the intensity and direction of SPGMs. A polarization-track method is proposed by using HIPMG for object tracking. Experiment results demonstrate the effectiveness of proposed feature extraction method over the state-of-the-art methods.",
keywords = "Feature Extraction, Infrared Polarization, Object Tracking",
author = "Xinbo Qiao and Lulu Chen and Yongqiang Zhao",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 10th International Conference on Computing and Pattern Recognition, ICCPR 2021 ; Conference date: 15-10-2021 Through 17-10-2021",
year = "2021",
month = oct,
day = "15",
doi = "10.1145/3497623.3497659",
language = "英语",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "224--230",
booktitle = "ICCPR 2021 - Proceedings of 2021 10th International Conference on Computing and Pattern Recognition",
}