Publications

Journal Papers

  • Ninghang Hu, Gwenn Englebienne, Zhongyu Lou, and Ben Kröse.
    Learning to Recognize Human Activities using Soft Labels.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2016.
    http://dx.doi.org/10.1109/TPAMI.2016.2621761
  • Zhongyu Lou, Fares Alnajar, Jose Alvarez, Ninghang Hu, and Theo Gevers.
    Expression-Invariant Age Estimation Using Structured Learning.
    IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2016.
    http://dx.doi.org/10.1109/TPAMI.2016.2621761
  • Ninghang Hu, Gwenn Englebienne, Zhongyu Lou, and Ben Kröse.
    Latent Hierarchical Model for Activity Recognition
    IEEE Transactions on Robotics (T-RO), 2015.
    doi: 10.1109/TRO.2015.2495002
  • Zhongyu Lou,Theo Gevers, and Ninghang Hu.
    Extracting 3D Layout From a Single Image Using Global Image Structures.
    IEEE Transactions on Image Processing (T-IP), 2015.
    http://dx.doi.org/10.1109/TIP.2015.2431443
  • F. Amirabdollahian, S. Bedaf, R. Bormann, et al.
    Assistive technology design and development for acceptable robotics companions for ageing years
    Journal of Behavioral Robotics, 2013.
    http://dx.doi.org/10.2478/pjbr-2013-0007

Conference Proceedings

  • N. Hu, A. Bestick, G. Englebienne, R, Bajcsy, B. Kröse, “Human Intent Forecasting Using Intrinsic Kinematic Constraints”, in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016. [To appear]
  • Y. Zhou, N. Hu, and C. Spanos, “Veto-Consensus Multiple Kernel Learning,” in AAAI, 2016. [http://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/12119]
  • N. Hu, Z. Lou, G. Englebienne, and B. Kröse, “A Hierarchical Representation for Human Activity Recognition with Noisy Labels”, in IEEE International Conference on Intelligent Robots and Systems (IROS), 2015.
    [http://dx.doi.org/10.1109/IROS.2015.7353719]
  • Z. Lou, T. Gevers, and N. Hu, “Color Constancy by Deep Learning,” in British Machine Vision Conference (BMVC), 2015.
    [https://dx.doi.org/10.5244/C.29.76]
  • N. Hu, Z. Lou, G. Englebienne, and B. Kröse, “Learning to Recognize Human Activities from Soft Labeled Data,” in Robotics: Science and Systems (RSS), 2014.
    [http://www.roboticsproceedings.org/rss10/p03.html, software]
  • N. Hu, G. Englebienne, Z. Lou, and B. Kröse, “Learning Latent Structure for Activity Recognition,” in IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2014, pp. 1048–1053.
    [http://dx.doi.org/10.1109/ICRA.2014.6906983software]
  • N. Hu, R. Bormann, T. Zwölfer, and B. Kröse, “Multi-User Identification and Efficient User Approaching by Fusing Robot and Ambient Sensors,” in IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2014, pp. 5299–5306.
    [http://dx.doi.org/10.1109/ICRA.2014.6907638]
  • N. Hu, G. Englebienne, Z. Lou, and B. Kröse, “A Two-layered Approach to Recognize High-level Human Activities,” in IEEE International Symposium on Robot and Human Interactive Communication (Ro-Man). IEEE, 2014, pp. 243–248.
    [http://dx.doi.org/10.1109/ROMAN.2014.6926260]
  • Amirabdollahian, F., Akker, R., Bedaf, S., et al., “Accompany: Acceptable robotiCs COMPanions for AgeiNG Years – Multidimensional aspects of human-system interactions,” IEEE International Conference on Human System Interaction (HSI), 2013 (Best Paper Award)
    [http://dx.doi.org/10.1109/HSI.2013.6577882]
  • N. Hu, G. Englebienne, and B. Kröse, “Posture recognition with a top-view camera,” in IEEE International Conference on Intelligent Robots and Systems (IROS). IEEE, 2013, pp. 2152–2157.
    [http://dx.doi.org/10.1109/IROS.2013.6696657]
  • N. Hu, H. Bouma, and M. Worring, “Tracking individuals in surveillance video of a high-density crowd,” in SPIE, vol. 8399, 2012, pp. 1–8.
    [http://dx.doi.org/10.1117/12.918604]

Workshop

  • N. Hu, G. Englebienne, and B. Kröse, “Bayesian fusion of ceiling mounted camera and laser range finder on a mobile robot for people detection and localization,” in IROS workshop, Human Behavior Understanding. Springer, 2012, pp. 41–51. [https://doi.org/10.1007/978-3-642-34014-7_4]
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