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  4. A Short Note on Analyzing Sequence Complexity in Trajectory Prediction Benchmarks
 
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2020
  • Vortrag

Titel

A Short Note on Analyzing Sequence Complexity in Trajectory Prediction Benchmarks

Titel Supplements
Accepted at LHMP 2020 Workshop (ICRA 2020)
Abstract
The analysis and quantification of sequence complexity is an open problem frequently encountered when defining trajectory prediction benchmarks. In order to enable a more informative assembly of a data basis, an approach for determining a dataset representation in terms of a small set of distinguishable prototypical sub-sequences is proposed. The approach employs a sequence alignment followed by a learning vector quantization (LVQ) stage. A first proof of concept on synthetically generated and real-world datasets shows the viability of the approach.
Author(s)
Hug, Ronny
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB
Becker, Stefan
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB
Hübner, Wolfgang
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB
Arens, Michael
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB
Konferenz
International Conference on Robotics and Automation (ICRA) 2020
Workshop on Long-term Human Motion Prediction (LHMP) 2020
File(s)
N-595921.pdf (1.93 MB)
Language
Englisch
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