Prasanth Sasikumar

Prasanth Sasikumar

PhD Student

Prasanth Sasikumar is a PhD candidate with particular interests in Multimodal input in Remote Collaboration and scene reconstruction. He received his Master’s degree in Human-Computer interaction at the University of Canterbury in 2017. For his Masters Thesis he has worked on incorporating wearable and non wearable Haptic devices in VR sponsored by MBIE as part of NZ/Korea Human-Digital Content Interaction for Immersive 4D Home Entertainment project. 

Prasanth has a keen interest in VR and AR applications and how they may assist industry to better solve problems. Currently, he is doing his PhD research under the supervision of Prof. Mark Billinghurst and Dr. Huidong Bai  in Empathic Computing Lab at the University of Auckland.

Publications

  • A User Study on Mixed Reality Remote Collaboration with Eye Gaze and Hand Gesture Sharing
    Huidong Bai , Prasanth Sasikumar , Jing Yang , Mark Billinghurst

    Huidong Bai, Prasanth Sasikumar, Jing Yang, and Mark Billinghurst. 2020. A User Study on Mixed Reality Remote Collaboration with Eye Gaze and Hand Gesture Sharing. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–13. DOI:https://doi.org/10.1145/3313831.3376550

    BibTexLinksAbstract
    @inproceedings{bai2020user,
    title={A User Study on Mixed Reality Remote Collaboration with Eye Gaze and Hand Gesture Sharing},
    author={Bai, Huidong and Sasikumar, Prasanth and Yang, Jing and Billinghurst, Mark},
    booktitle={Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems},
    pages={1--13},
    year={2020}
    }
    View: https://dl.acm.org/doi/abs/10.1145/3313831.3376550
    Supporting natural communication cues is critical for people to work together remotely and face-to-face. In this paper we present a Mixed Reality (MR) remote collaboration system that enables a local worker to share a live 3D panorama of his/her surroundings with a remote expert. The remote expert can also share task instructions back to the local worker using visual cues in addition to verbal communication. We conducted a user study to investigate how sharing augmented gaze and gesture cues from the remote expert to the local worker could affect the overall collaboration performance and user experience. We found that by combing gaze and gesture cues, our remote collaboration system could provide a significantly stronger sense of co-presence for both the local and remote users than using the gaze cue alone. The combined cues were also rated significantly higher than the gaze in terms of ease of conveying spatial actions.