Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Yuthika Punchihewa"'
Autor:
Yuthika Punchihewa, Ba-Tuong Vo, Ba-Ngu Vo, Amanda Bessell, Sanjeev Arulampalam, Jessica Irons, Sam Davey
Publikováno v:
2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::21623b5c6a0473e78e819012cc4f4ce4
https://doi.org/10.1109/iccais56082.2022.9990136
https://doi.org/10.1109/iccais56082.2022.9990136
Publikováno v:
2022 11th International Conference on Control, Automation and Information Sciences (ICCAIS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b228261ca7b4a9c56e8036fff441dfad
https://doi.org/10.1109/iccais56082.2022.9990410
https://doi.org/10.1109/iccais56082.2022.9990410
Multi-target state estimation refers to estimating the number of targets and their trajectories in a surveillance area using measurements contaminated with noise and clutter. In the Bayesian paradigm, the most common approach to multi-target estimati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce09e63a234a160e7326329e86c13962
Autor:
Yuthika Punchihewa
Publikováno v:
ICCAIS
This paper proposes efficient implementations for a Generalized Labeled Multi-Bernoulli filter for a Jump Markov System. The proposed filter operates via combining both prediction and update steps into a single step, therefore requiring merely a sing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7109209c14b0e06fb9af2397f18f7e6b
https://doi.org/10.1109/iccais.2017.8217580
https://doi.org/10.1109/iccais.2017.8217580
This paper proposes an on-line multiple object tracking algorithm that can operate in unknown background. In a majority of multiple object tracking applications, model parameters for background processes such as clutter and detection are unknown and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3b37247a114f551fd95570a8e8a7a18
http://arxiv.org/abs/1706.01584
http://arxiv.org/abs/1706.01584
Publikováno v:
ICCAIS
This paper demonstrates how the δ-Generalized Labeled Multi-Bernoulli (δ-GLMB) filter can be applied to track moving targets on videos. The tracking is performed directly on the original images which are not preprocessed into point measurements and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1683e14253500ce117c2ba86ef609101
https://doi.org/10.1109/iccais.2014.7020543
https://doi.org/10.1109/iccais.2014.7020543