conference paper · International Conference on Consumer Electronics · 2012
Moving object detection strategy for augmented-reality applications in a GPGPU by using CUDA
Daniel Berjón, Carlos Cuevas, Francisco Morán, Narciso N. Garcia
Cited by 2Open access
Abstract
A spatial-color-based non-parametric background-foreground modeling strategy in a GPGPU by using CUDA is proposed. This strategy is suitable for augmented-reality applications, providing real-time high-quality results in a great variety of scenarios.
Cite this paper
Berjón, D., Cuevas, C., Morán, F., & Garcia, N. N. (2012). Moving object detection strategy for augmented-reality applications in a GPGPU by using CUDA. International Conference on Consumer Electronics, 9, 319–320. https://doi.org/10.1109/icce.2012.6161886
Berjón, Daniel, et al. “Moving object detection strategy for augmented-reality applications in a GPGPU by using CUDA.” International Conference on Consumer Electronics, vol. 9, 2012, pp. 319–20, https://doi.org/10.1109/icce.2012.6161886.
Berjón, Daniel, Carlos Cuevas, Francisco Morán, and Narciso N. Garcia. 2012. “Moving object detection strategy for augmented-reality applications in a GPGPU by using CUDA.” International Conference on Consumer Electronics 9: 319–20. https://doi.org/10.1109/icce.2012.6161886.
Berjón, D. et al. (2012) ‘Moving object detection strategy for augmented-reality applications in a GPGPU by using CUDA’, International Conference on Consumer Electronics, 9, pp. 319–320. Available at: https://doi.org/10.1109/icce.2012.6161886.
@article{berjon2012moving,
title = {{Moving object detection strategy for augmented-reality applications in a GPGPU by using CUDA}},
author = {Berjón, Daniel and Cuevas, Carlos and Morán, Francisco and Garcia, Narciso N.},
journal = {International Conference on Consumer Electronics},
volume = {9},
pages = {319--320},
year = {2012},
doi = {10.1109/icce.2012.6161886}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.