Virtual Reality Technologies (Visual, Haptics, and Audio) in Large Datasets Analysis

Virtual Reality Technologies (Visual, Haptics, and Audio) in Large Datasets Analysis

Bob-Antoine J. Menelas (University of Quebec at Chicoutimi, Canada)
Copyright: © 2014 |Pages: 22
DOI: 10.4018/978-1-4666-4309-3.ch006
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Abstract

With the latest developments in technology, several researchers have integrated other sensorymotor channels in the analysis of scientific datasets. In addition to vision, auditory feedbacks and haptic interactions have been exploited. In this chapter we study how these modalities can contribute to effective analysis processes. Based on psychophysical characteristics of humans the author argues that haptics should be used in order to improve interactions of the user with the dataset to analyze. The author describes a classification that highlights four tasks for which haptics seems to present advantages over vision and audio. Proposed taxonomy is divided into four categories: Select, Locate, Connect and Arrange. Moreover, this work provides a complete view on the contribution of haptics in analysis of scientific datasets.
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Potential Of Vr Technologies For Analysis Of Large Datasets

First, visualization applications range from non-interactive to command-driven systems. In such systems, commands are sent, processed and then comes the result. However, the need to interact with the system has emerged quickly. For example, one would like to zoom, rotate or filter the data. At this point starts the fusion, the interleaving between the query and the result via an iterative process. From there, data analysis is not only guided by the need for effective presentation of data: there are two main components that are the presentation and interaction.

At this point, Shneiderman (1996) identifies four main steps for the implementation of effective interaction process: Overview first, zoom, filter, then details-on-demand. Recently, Yi et al. (2007) have suggested that the interaction process can be supported through seven types of interaction based on users’ intent while interacting with the system. For several researchers of the field, as part of the Human Computer Interaction (HCI) domain, interactive visualization aims at offering a direct and bidirectional communication between people (users) and the visualization system. Bryson (1996) stated that the goal is to create the effect of interacting with things, not with pictures of things. This approach establishes a clear difference between the user and the system: “the user interacts with the system”.

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