Data-driven Haptic Feedback Utilizing an Object Manipulation Data-set


This study presents an ongoing work on a new large-scale, user-object interaction data-set incorporating visual, sensorial and positional modalities, which can potentially be used for (a) assessing vision-related machine learning models for different tasks targeting scene understanding, such as activity recognition, visual object affordances and object detection; (b) providing realistic interactions in the Virtual Reality (VR) world; (c) enhancing 3D perception in robotic applications such as manipulation. The aim is to provide a large and diverse set of stereo video sequences, filmed from multiple cameras and involving multiple actors, together with sensorial and positional data recorded in our lab’s premises. The data-set is utilized as a first effort to provide realistic haptic feedback to a user interacting with a 3D object in a virtual environment. This data-set is expected to bridge the aforementioned gap between theory and application and facilitate the development of techniques which allow robots to better understand their surroundings. A set of experiments and a preliminary analysis show promising results and demonstrate the particular characteristics of the involved representation schemes.

  • A. Ntovas, L. Lazaridis, A. Papadimitriou, A. Psaltis, A. Axenopoulos, P. Daras, "Data-driven Haptic Feedback Utilizing an Object Manipulation Data-set", in IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June, 2021.

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    Contact Information

    Dr. Petros Daras, Research Director
    6th km Charilaou – Thermi Rd, 57001, Thessaloniki, Greece
    P.O.Box: 60361
    Tel.: +30 2310 464160 (ext. 156)
    Fax: +30 2310 464164
    Email: daras(at)iti(dot)gr