Abstract
Many systems use visual devices to detect, inspect and analyze persons, scenes, and properties of objects. Often, they use samples to learn relevant indicators to reach a high level of quality of the appropriated operation. Nevertheless, collecting samples and annotate the relevant parts may be a hard, expensive and error prone task in same fields of use. To overcome this problem we create a system to generate synthetic scenarios based on predefined and exact definitions of the content as well as the sample production process. To demonstrate the usability we apply a scenario with a humanoid with known activity and with various environment objects to different systems for visual detection and analysis.
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References
Hägele, M., Schaaf, W., Helms, E.: Robot assistants at manual workplaces: effective cooperation and safety aspects. In: Proceedings of the 33rd International Symposium on Robotics, pp. 1–6 (2002)
Germa, T., Lerasle, F., Danes, P., Brethes, L.: Human/robot visual interaction for a tour-guide robot. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3448–3453. IEEE Press (2007)
Bilenko, M., Kamath, B., Mooney, R.J.: Adaptive blocking: learning to scale up record linkage. In: Universal Access in Human-Computer Interaction, pp. 460–467. Springer, Heidelberg (2016)
Manthey, R., Conrad, C., Ritter, M.: A framework for generation of testsets for recent multimedia workflows. In: Proceedings of the 6th IEEE International Conference on Data Mining, pp. 87–96. IEEE Press (2006)
Acknowledgements
This work was partially accomplished within the project localizeIT (funding code 03IPT608X) funded by the Federal Ministry of Education and Research (BMBF, Germany) in the program of Entrepreneurial Regions InnoProfile-Transfer.
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Manthey, R. et al. (2019). Visual System Examination Using Synthetic Scenarios. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration 2019. IHSI 2019. Advances in Intelligent Systems and Computing, vol 903. Springer, Cham. https://doi.org/10.1007/978-3-030-11051-2_63
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DOI: https://doi.org/10.1007/978-3-030-11051-2_63
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