Related papers: HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area Surveillance

HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area Surveillance

URL: http://arxiv.org/abs/2204.04435v1
Date: Sat, 9 Apr 2022 09:23:58 GMT
Title: HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area Surveillance
Authors: H. Umut Suluhan, Hasan F. Ates, Bahadir K. Gunturk
Abstract summary: This paper presents the usage of multiple video feeds for the generation of HSTR video. The main purpose is to create an HSTR video from the fusion of HSLF and LSHF videos.
Score: 4.125187280299246
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: Wide area surveillance has many applications and tracking of objects under observation is an important task, which often needs high spatio-temporal resolution (HSTR) video for better precision. 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 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 objective PSNR and SSIM metrics.

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