Sparse Optical Flow Implementation Using a Neural Network for Low-Resolution Thermal Aerial Imaging

This study is inspired by the widely used algorithm for real-time optical flow, the sparse Lucas–Kanade, by applying a feature extractor to decrease the computational requirement of optical flow based neural networks from real-world thermal aerial imagery. Although deep-learning-based algorithms hav...

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Detalles Bibliográficos
Autores principales: Nguyen, Tran Xuan Bach, Chahl, Javaan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605610/
https://www.ncbi.nlm.nih.gov/pubmed/36286373
http://dx.doi.org/10.3390/jimaging8100279

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605610/
https://www.ncbi.nlm.nih.gov/pubmed/36286373
http://dx.doi.org/10.3390/jimaging8100279

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