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DFKI Cabin Simulator: A Test Platform for Visual In-Cabin Monitoring Functions

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Commercial Vehicle Technology 2020/2021

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Abstract

We present a test platform for visual in-cabin scene analysis and occupant monitoring functions. The test platform is based on a driving simulator developed at the DFKI, consisting of a realistic in-cabin mock-up and a wide-angle projection system for a realistic driving experience. The platform has been equipped with a wide-angle 2D/3D camera system monitoring the entire interior of the vehicle mock-up of the simulator. It is also supplemented with a ground truth reference sensor system that allows to track and record the occupant’s body movements synchronously with the 2D and 3D video streams of the camera. Thus, the resulting test platform will serve as a basis to validate numerous incabin monitoring functions, which are important for the realization of novel human-vehicle interfaces, advanced driver assistant systems, and automated driving. Among the considered functions are occupant presence detection, size and 3D-pose estimation, and driver intention recognition. In addition, our platform will be the basis for the creation of large-scale in-cabin benchmark datasets.

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References

  1. Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B.: 2d human pose estimation: New benchmark and state of the art analysis. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2014)

    Google Scholar 

  2. Cruz, S.D.D., Wasenmüller, O., Beise, H.P., Stifter, T., Stricker, D.: Sviro: Synthetic vehicle interior rear seat occupancy dataset and benchmark. In: IEEE Winter Conference on Applications of Computer Vision (WACV) (2020)

    Google Scholar 

  3. Elhayek, A., Kovalenko, O., Murthy, P., Malik, J., Stricker, D.: Fully automatic multi-person human motion capture for VR applications. In: Virtual Reality and Augmented Reality - 15th EuroVR International Conference, EuroVR 2018, London, UK, October 22-23, 2018, Proceedings. pp. 28–47 (2018), https://doi.org/https://doi.org/10.1007/978-3-030-01790-3 3

  4. Firman, M.: RGBD Datasets: Past, Present and Future. In: CVPR Workshop on Large Scale 3D Data: Acquisition, Modelling and Analysis (2016)

    Google Scholar 

  5. Habibie, I., Xu, W., Mehta, D., Pons-Moll, G., Theobalt, C.: In the wild human pose estimation using explicit 2d features and intermediate 3d representations. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)

    Google Scholar 

  6. Math, R., Mahr, A., Moniri, M.M., Muller, C.: Opends: A new open-source driving simulator for research. In: GMM-Fachbericht-AmE 2013 (2013)

    Google Scholar 

  7. Microsoft: Kinect camera. https://www.xbox.com/en-US/kinect/default.htm (2010), last accessed 2019/12/04 via https://web.archive.org

  8. Microsoft: Kinect for windows v2. https://support.xbox.com/en-US/xbox-onwindows/accessories/kinect-for-windows-v2-info (2014), last accessed 2019/12/04

  9. Microsoft: Azure kinect camera. https://azure.microsoft.com/enin/services/kinect-dk/ (2019), last accessed 2019/12/04

  10. Murthy, P.N., Kovalenko, O., Elhayek, A., Couto Gava, C., Stricker, D.: 3d human pose tracking inside car using single rgb spherical camera. In: ACM Chapters Computer Science in Cars Symposium (CSCS) (2017)

    Google Scholar 

  11. MYNTAI: Mynt eye S camera. https://www.mynteye.com/products/mynt-eyestereo-camera (2018), last accessed 2019/12/04

  12. NaturalPoint: Optitrack 3d tracking system. https://optitrack.com/, last accessed 2019/12/04

  13. Occipital: Structure core camera. https://structure.io/structure-core (2018), last accessed 2019/12/04

  14. Ren, S., He, K., Girshick, R., Sun, J.: Faster r-cnn: Towards realtime object detection with region proposal networks. IEEE Transactions on Pattern Analysis and Machine Intelligence 39(6), 1137–1149 (2017), http://dx.doi.org/https://doi.org/10.1109/TPAMI.2016.2577031

  15. Roth, M., Gavrila, D.M.: Dd-pose - a large-scale driver head pose benchmark. In: IEEE Intelligent Vehicles Symposium (2019)

    Google Scholar 

  16. Schwarz, A., Haurilet, M., Martinez, M., Stiefelhagen, R.: Driveahead - a large-scale driver head pose dataset. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)

    Google Scholar 

  17. Selim, M., Firintepe, A., Pagani, A., Stricker, D.: Autopose: Large-scale automotive driver head pose and gaze dataset with deep head pose baseline. In: Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISAPP (2020)

    Google Scholar 

  18. Shotton, J., Fitzgibbon, A., Blake, A., Kipman, A., Finocchio, M., Moore, B., Sharp, T.: Real-time human pose recognition in parts from a single depth image. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2011)

    Google Scholar 

  19. Stereolabs: Stereolabs zed camera. https://www.stereolabs.com/zed/ (2015), last accessed 2019/12/04

  20. Tewari, A., Taetz, B., Grandidier, F., Stricker, D.: A probabilistic combination of cnn and rnn estimates for hand gesture based interaction in car. In: IEEE International Symposium on Mixed and Augmented Reality (ISMAR) (2017)

    Google Scholar 

  21. VIVA: Vision for intelligent vehicles and applications. https://cvrr.ucsd.edu/vivachallenge/ (2016), last accessed 2019/07/25

  22. Wasenmüller, O., Meyer, M., Stricker, D.: CoRBS: Comprehensive rgb-d benchmark for slam using kinect v2. In: IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE (2016), https://corbs.dfki.uni-kl.de/

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Correspondence to Hartmut Feld .

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© 2021 Der/die Autor(en), exklusiv lizenziert durch Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

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Feld, H., Mirbach, B., Katrolia, J., Selim, M., Wasenmüller, O., Stricker, D. (2021). DFKI Cabin Simulator: A Test Platform for Visual In-Cabin Monitoring Functions. In: Berns, K., Dressler, K., Kalmar, R., Stephan, N., Teutsch, R., Thul, M. (eds) Commercial Vehicle Technology 2020/2021. Proceedings. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-29717-6_28

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