Dual camera based high spatio-temporal resolution video generation for wide area surveillance

Name: Dual camera based high spatio-temporal resolution video generation for wide area surveillance
Author: Suluhan, Hasan Umut, Ates, H. F., Gunturk, B. K.

İsim	Dual camera based high spatio-temporal resolution video generation for wide area surveillance
Yazar	Suluhan, Hasan Umut, Ates, H. F., Gunturk, B. K.
Basım Tarihi:	2022
Basım Yeri	- IEEE
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-166546382-9
Kayıt Numarası	04bc2674-17c2-483e-856c-fdd97037bccb
Tarih	2022
Notlar	TÜBİTAK
Örnek Metin	Wide area surveillance (WAS) requires high spatiotemporal resolution (HSTR) video for better precision. As an alternative to expensive WAS systems, low-cost hybrid imaging systems can be used. This paper presents the usage of multiple video feeds for the generation of HSTR video as an extension of reference based super resolution (RefSR). One feed captures video at high spatial resolution with low frame rate (HSLF) while the other captures low spatial resolution and high frame rate (LSHF) video simultaneously for the same scene. The main purpose is to create an HSTR video from the fusion of HSLF and LSHF videos. In this paper we propose an end-to-end trainable deep network that performs optical flow (OF) estimation and frame reconstruction by combining inputs from both video feeds. The proposed architecture provides significant improvement over existing video frame interpolation and RefSR techniques in terms of PSNR and SSIM metrics and can be deployed on drones with dual cameras.
DOI	10.1109/AVSS56176.2022.9959711

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Dual camera based high spatio-temporal resolution video generation for wide area surveillance

Yazar Suluhan, Hasan Umut, Ates, H. F., Gunturk, B. K.

Basım Tarihi 2022

Basım Yeri - IEEE

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-166546382-9

Kayıt Numarası 04bc2674-17c2-483e-856c-fdd97037bccb

Tarih 2022

Notlar TÜBİTAK

Örnek Metin Wide area surveillance (WAS) requires high spatiotemporal resolution (HSTR) video for better precision. As an alternative to expensive WAS systems, low-cost hybrid imaging systems can be used. This paper presents the usage of multiple video feeds for the generation of HSTR video as an extension of reference based super resolution (RefSR). One feed captures video at high spatial resolution with low frame rate (HSLF) while the other captures low spatial resolution and high frame rate (LSHF) video simultaneously for the same scene. The main purpose is to create an HSTR video from the fusion of HSLF and LSHF videos. In this paper we propose an end-to-end trainable deep network that performs optical flow (OF) estimation and frame reconstruction by combining inputs from both video feeds. The proposed architecture provides significant improvement over existing video frame interpolation and RefSR techniques in terms of PSNR and SSIM metrics and can be deployed on drones with dual cameras.

DOI 10.1109/AVSS56176.2022.9959711