Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):
R. Repp, G. Koliander, F. Meyer, F. Hlawatsch:
"Local detection and estimation of multiple objects from images with overlapping observation areas";
Poster: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2017),
New Orleans, Louisiana, USA;
05.03.2017
- 09.03.2017; in: "2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
IEEE (Hrg.);
(2017),
S. 4641
- 4645.
Kurzfassung englisch:
We propose a method for detecting and estimating multiple objects from multiple noisy images with partly overlapping observation areas. The goal is to detect the objects that are "locally" present in the individual observation areas and to estimate their states. Our method is based on a new closed-form expression of the marginal posterior probability hypothesis density (PHD) and admits a distributed implementation. Simulation results demonstrate performance gains over correlation-based and PHD-based methods that do not take advantage of the overlapping observation areas.
Schlagworte:
Random finite set, FISST, probability hypothesis density, PHD, image processing
"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/ICASSP.2017.7953036
Elektronische Version der Publikation:
http://publik.tuwien.ac.at/files/publik_263013.pdf
Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.