Cargando…
Advances in real-time object tracking: Extensions for robust object tracking with a Monte Carlo particle filter
The huge amount of literature on real-time object tracking continuously reports good results with respect to accuracy and robustness. However, when it comes to the applicability of these approaches to real-world problems, often no clear statements about the tracking situation can be made. This paper...
Autores principales: | Mörwald, Thomas, Prankl, Johann, Zillich, Michael, Vincze, Markus |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089693/ https://www.ncbi.nlm.nih.gov/pubmed/32226554 http://dx.doi.org/10.1007/s11554-013-0388-4 |
Ejemplares similares
-
Learning of perceptual grouping for object segmentation on RGB-D data()
por: Richtsfeld, Andreas, et al.
Publicado: (2014) -
Interactive object modelling based on piecewise planar surface patches()
por: Prankl, Johann, et al.
Publicado: (2013) -
Multiple object-tracking isolates feedback-specific load in attention and learning
por: Tullo, Domenico, et al.
Publicado: (2020) -
Robust Scale Adaptive Tracking by Combining Correlation Filters with Sequential Monte Carlo
por: Ma, Junkai, et al.
Publicado: (2017) -
Robust Visual Tracking with Reliable Object Information and Kalman Filter
por: Chen, Hang, et al.
Publicado: (2021)