@InProceedings{abderrahmane:icarcv:2018,
  author    = {Abderrahmane, Zineb and Ganesh, Gowrishankar and Crosnier, Andr{\'e} and Cherubini, Andrea},
  title     = {Visuo-Tactile Recognition of Daily-Life Objects Never Seen or Touched Before},
  booktitle = {International Conference on Control, Automation, Robotics and Vision},
  year      = {2018},
  address   = {Singapore},
  month     = {November 18-November 21},
  url       = {https://hal.archives-ouvertes.fr/hal-01869015/document},
  keywords  = {Visualization, Robot sensing systems, Haptic interfaces, Training data, Feature extraction},
  doi       = {10.1109/ICARCV.2018.8581230},
  abstract  = {This study proposes a visuo-tactile Zero-Shot object recognition framework. The proposed framework recognizes a set of novel objects for which no tactile or visual training data are available. It uses visuo-tactile training data collected from known objects to recognize the novel ones, given their attributes. This framework extends the haptic Zero-Shot Learning framework that we proposed in [1] with vision, which enables a multimodal recognition system. In our test with the PHAC-2 dataset, the system was able to get a recognition accuracy of 72\% among 6 objects that were never touched or seen during the training phase.}
}