arXiv Open Access 2023

A real-time algorithm for human action recognition in RGB and thermal video

Hannes Fassold Karlheinz Gutjahr Anna Weber Roland Perko

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Abstrak

Monitoring the movement and actions of humans in video in real-time is an important task. We present a deep learning based algorithm for human action recognition for both RGB and thermal cameras. It is able to detect and track humans and recognize four basic actions (standing, walking, running, lying) in real-time on a notebook with a NVIDIA GPU. For this, it combines state of the art components for object detection (Scaled YoloV4), optical flow (RAFT) and pose estimation (EvoSkeleton). Qualitative experiments on a set of tunnel videos show that the proposed algorithm works robustly for both RGB and thermal video.

Topik & Kata Kunci

cs.CV

Penulis (4)

Hannes Fassold

Karlheinz Gutjahr

Anna Weber

Roland Perko

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APA MLA BibTeX

Fassold, H., Gutjahr, K., Weber, A., Perko, R. (2023). A real-time algorithm for human action recognition in RGB and thermal video. https://arxiv.org/abs/2304.01567

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Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓