A comparison of different haptic compression techniques

Immersive environments provide an artificial world to surround users. These environments consist of a composition of various types of immersidata: unique data types that are combined to render a virtual experience. To construct such an environment, immersidata acquisition is indispensable for storage and future query. However, this is challenging because of the real time demands and sizeable amounts of data to be managed. We propose and evaluate alternative techniques for achieving efficient sampling and compression of one immersidata type, the haptic data, which describes the movement, rotation, and force associated with user-directed objects in an immersive environment. Our experiments identify the benefits and limitations of various techniques in terms of their data storage, bandwidth and accuracy.