Jorge Ribeiro - Academia.edu (original) (raw)
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Papers by Jorge Ribeiro
MobiQuitous 2020 - 17th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2020
In this work we present three prototypes of the tangible VR Book: a visual marker-based solution ... more In this work we present three prototypes of the tangible VR Book: a visual marker-based solution to tangible interaction for smartphonebased Virtual Reality (VR). Smartphone-based VR represents a low barrier to entry in VR experiences given that many people nowadays own a smartphone device and that VR headsets for these devices are affordable and quick to set up when compared to desktopbased VR. Tangible interaction in smartphone-based VR has not been much explored, in our opinion, despite the fact that it can result in easy to use and engaging experiences. In this work, we explore a marker-based solution to object tracking that allows tangibles to be created in an easy and cheap way, maintaining the overall system accessible. We describe a design space for visual marker-based tangible interaction and three prototypes of a tangible VR Book that explore different aspects of the design space. We also present user feedback on their expectations regarding the interaction with the VR Book. CCS CONCEPTS • Human-centered computing → Virtual reality; Smartphones; Ubiquitous and mobile computing design and evaluation methods.
In this paper, a handover motion reconstruction methodology is presented. First to be examined in... more In this paper, a handover motion reconstruction methodology is presented. First to be examined in the proposed approach is the way in which the system computes the optimal markerset for a given dataset of hand motion sequences. In a second step before the motion reconstruction process and given the reduced number of markers, the system estimates the remaining markers by computing a simple distance metric. Having the complete number of markers, including both the input and the computed markers, the system reconstructs the motion of the character's fingers. The reconstruction process is formulated in a maximum a posteriori framework, which is responsible for approximating a valid pose of the character's hand, in which the mixture of factor analysis (MFA) clustering techniques was used for the prior learning process. The results show that high quality motions of the character's hand can be reconstructed with the methodology presented.
MobiQuitous 2020 - 17th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2020
In this work we present three prototypes of the tangible VR Book: a visual marker-based solution ... more In this work we present three prototypes of the tangible VR Book: a visual marker-based solution to tangible interaction for smartphonebased Virtual Reality (VR). Smartphone-based VR represents a low barrier to entry in VR experiences given that many people nowadays own a smartphone device and that VR headsets for these devices are affordable and quick to set up when compared to desktopbased VR. Tangible interaction in smartphone-based VR has not been much explored, in our opinion, despite the fact that it can result in easy to use and engaging experiences. In this work, we explore a marker-based solution to object tracking that allows tangibles to be created in an easy and cheap way, maintaining the overall system accessible. We describe a design space for visual marker-based tangible interaction and three prototypes of a tangible VR Book that explore different aspects of the design space. We also present user feedback on their expectations regarding the interaction with the VR Book. CCS CONCEPTS • Human-centered computing → Virtual reality; Smartphones; Ubiquitous and mobile computing design and evaluation methods.
In this paper, a handover motion reconstruction methodology is presented. First to be examined in... more In this paper, a handover motion reconstruction methodology is presented. First to be examined in the proposed approach is the way in which the system computes the optimal markerset for a given dataset of hand motion sequences. In a second step before the motion reconstruction process and given the reduced number of markers, the system estimates the remaining markers by computing a simple distance metric. Having the complete number of markers, including both the input and the computed markers, the system reconstructs the motion of the character's fingers. The reconstruction process is formulated in a maximum a posteriori framework, which is responsible for approximating a valid pose of the character's hand, in which the mixture of factor analysis (MFA) clustering techniques was used for the prior learning process. The results show that high quality motions of the character's hand can be reconstructed with the methodology presented.