Spatio-temporal categorization for first-person-view videos using a convolutional variational autoencoder and Gaussian processes

In this study, HcVGH, a method that learns spatio-temporal categories by segmenting first-person-view (FPV) videos captured by mobile robots, is proposed. Humans perceive continuous high-dimensional information by dividing and categorizing it into significant segments. This unsupervised segmentation...

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Detalles Bibliográficos
Autores principales: Nagano, Masatoshi, Nakamura, Tomoaki, Nagai, Takayuki, Mochihashi, Daichi, Kobayashi, Ichiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Robotics and AI
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562109/
https://www.ncbi.nlm.nih.gov/pubmed/36246490
http://dx.doi.org/10.3389/frobt.2022.903450

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9562109/
https://www.ncbi.nlm.nih.gov/pubmed/36246490
http://dx.doi.org/10.3389/frobt.2022.903450

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