Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition

Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (...

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Detalles Bibliográficos
Autores principales: Lin, Jia, Ruan, Xiaogang, Yu, Naigong, Yang, Yee-Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5191150/
https://www.ncbi.nlm.nih.gov/pubmed/27999337
http://dx.doi.org/10.3390/s16122171

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5191150/
https://www.ncbi.nlm.nih.gov/pubmed/27999337
http://dx.doi.org/10.3390/s16122171

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