Using cursor prediction to smooth telepointer jitter

Abstract

Telepointers are an important type of embodiment in real-time distributed groupware. Telepointers can increase the presence of remote participants and can provide considerable awareness information about people's locations and activities. However, the motion of a telepointer is often disrupted by network jitter. Although some strategies exist for dealing with jitter, none of these techniques are able to restore the immediacy and smoothness of a real cursor. In this paper we investigate the use of prediction -commonly used in networked simulations and games -to reduce the effects of jitter on telepointer motion. To determine whether prediction can be effective for improving telepointers, we carried out two experiments that tested the effects of different prediction schemes (some real and some artificial) on people's ability to interpret telepointer gestures. These studies show that although cursor prediction is still a difficult problem, there are both potential performance improvements, and definite preference advantages. Our studies suggest that telepointer prediction should be routinely used to increase the immediacy and naturalness of remote interaction, and suggest that prediction can also improve interpretation in certain situations.

Digital rubbing

“…For short strokes of around 1~2cm, it was about 10cm/sec on average. However, for long strokes of around 10~15cm, it A basic dead-reckoning technique was used in order to overcome the system delay problem [6]. Because rubbing is a regular and periodic movement, it is possible to predict the location of TransPen for a short amount of time.…”

On the error modeling of dead reckoned data in a distributed virtual environment

“…AMaze [1], DIVE [8], and NPSnet [15] in- troduced dead reckoning to improve real-time interactivity or to reduce the amount of data transmission. Effects on dead reckoning on temporal jitter of telepointers in realtime distributed groupware have been investigated in reference [7]. In reference [2][3], a dead reckoning method has been applied to streaming virtual human animation on networked virtual environments.…”

“…Our way of analysis is to introduce a mathematical model of this degradation with regard to the metrics of the temporal interval. A number of studies on the effects of using a dead reckoning method in real-time systems have previously been reported [1] [2][3] [7][8] [12] [15] [17] [19] [20]. However, theoretical evaluation of the dead reckoning method has not been sufficiently done.…”

Towards self-optimizing collaborative systems

“…We present a new collaborative framework that can take advantage of this opportunity and meet performance criteria better than existing systems without requiring hardware, network, or user-interface changes. Several performance metrics have been identified, such as local [14] and remote [4] response time, throughput [5], bandwidth [7], jitter [6], task completion time [2], and frame rate [16]. While all of them are important, our focus is on response times.…”