Collaborative virtual training using force feedback devices

Rodriguês, Maria Andréia Formico; Chaves, Ricardo Régis Cavalcante; Silva, W.B.

doi:10.1109/sibgra.2004.1352978

Cited by 8 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using our prototype, it is also possible to record a training session for later playback through a synchronization layer. A comprehensive description of the system architecture can be found in [Rodrigues et al 2004].…”

Section: System Architecturementioning

confidence: 99%

“…Therefore, in this work, motivated by the possibility of not only navigating and interacting remotely in a CVE, but as well as simulating and sharing the perception of contact forces among users in different 3D scenarios, a CVE system using force feedback devices we have previously presented [Rodrigues et al 2004] was tested extensively. We proposed and used a virtual training exercise, which was performed through the use of a pre-recorded animation path.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Performance and user based analysis of a collaborative virtual environment system

Rodriguês

Chaves

2007

Proceedings of the 5th International Conference on Computer Graphics and Interactive Techniques in Australia and Southeast Asia

View full text Add to dashboard Cite

In this work, we analyse the effect of network parameters on the judged usability of a collaborative virtual environment. Participants were trained to find the exit of a virtual maze by a trainer, which guided the exploration of the virtual space. An extensive experimental evaluation was conducted by simulating a series of operational parameters (network bandwidth and latency) to assess the reported effectiveness of the training. An objective similarity metric based on processing time per test was also defined and used, as well as subjective user's evaluations. Further, we have successfully correlated subjective evaluation and objective measure by computing the correlation values and showing how the two values co-vary.

show abstract

Section: System Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%