RuDaCoP: The Dataset for Smartphone-based Intellectual Pedestrian Navigation
| Autor: | Mikhail Pikhletsky, Alexey V. Derevyankin, Ilya Gartseev, Alexey Nikulin, Andrey Bayev, Ivan Chistyakov |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Ground truth Computer Science - Machine Learning Inertial frame of reference Computer science business.industry 010401 analytical chemistry 0206 medical engineering 02 engineering and technology Systems and Control (eess.SY) 020601 biomedical engineering 01 natural sciences Electrical Engineering and Systems Science - Systems and Control 0104 chemical sciences Machine Learning (cs.LG) Units of measurement Pedestrian navigation Trajectory FOS: Electrical engineering electronic engineering information engineering Computer vision Artificial intelligence business |
| Zdroj: | IPIN |
| DOI: | 10.48550/arxiv.1908.03609 |
| Popis: | This paper presents the large and diverse dataset for development of smartphone-based pedestrian navigation algorithms. This dataset consists of about 1200 sets of inertial measurements from sensors of several smartphones. The measurements are collected while walking through different trajectories up to 10 minutes long. The data are accompanied by the high accuracy ground truth collected with two foot-mounted inertial measurement units and post-processed by the presented algorithms. The dataset suits both for training of intellectual pedestrian navigation algorithms based on learning techniques and for development of pedestrian navigation algorithms based on classical approaches. The dataset is accessible at http://gartseev.ru/projects/ipin2019. |
| Databáze: | OpenAIRE |
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