Talks and Poster Presentations (with Proceedings-Entry):
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;
- 03-09-2017; in: "2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
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.
Random finite set, FISST, probability hypothesis density, PHD, image processing
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.