Enlargement of the Field of View Based on Image Region Prediction Using Thermal Videos

Ganbayar Batchuluun, Na Rae Baek and Kang Ryoung Park
Additional contact information
Ganbayar Batchuluun: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 04620, Korea
Na Rae Baek: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 04620, Korea
Kang Ryoung Park: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 04620, Korea

Mathematics, 2021, vol. 9, issue 19, 1-29

Abstract: Various studies have been conducted for detecting humans in images. However, there are the cases where a part of human body disappears in the input image and leaves the camera field of view (FOV). Moreover, there are the cases where a pedestrian comes into the FOV as a part of the body slowly appears. In these cases, human detection and tracking fail by existing methods. Therefore, we propose the method for predicting a wider region than the FOV of a thermal camera based on the image prediction generative adversarial network version 2 (IPGAN-2). When an experiment was conducted using the marathon subdataset of the Boston University-thermal infrared video benchmark open dataset, the proposed method showed higher image prediction (structural similarity index measure (SSIM) of 0.9437) and object detection (F1 score of 0.866, accuracy of 0.914, and intersection over union (IoU) of 0.730) accuracies than state-of-the-art methods.

Keywords: image prediction; thermal videos; deep learning; IPGAN-2 (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/19/2379/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/19/2379/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:19:p:2379-:d:642737

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().