Online 3D games require fast and efficient user interaction support over the network environments, and the networking support is usually implemented by the use of a network game engine. The network game engine should minimize the network delay and mitigate the network traffic congestion. To minimize the network traffic between game users, a client-based prediction (dead reckoning (DR) algorithm) is used. Each game entity uses the algorithm to estimate its own movement as well as the others’. In case the estimation error exceeds the threshold, the entity sends an UPDATE packet which includes velocity, position and the like to other entities. As the estimation accuracy is increased, each entity can minimize the transmission of the UPDATE packet. In this paper, a Kalman filter-based approach is proposed in order to improve the prediction accuracy and an adaptive Kalman gain control in order to minimize the number of UPDATE packets to distant devices. The BZFlag game was used in the experiment in order to verify the proposed approach and the results have shown that it is possible to increase prediction accuracy and reduce the network traffic by 12%.

We designed and tested the effects of an in-car augmented reality system (ARS) on younger and older drivers, with and without a secondary distraction task. When potential danger is detected, the ARS alerts the driver by progressively indicating the time to collision to the lead vehicle as well as merging vehicles from side lanes by an AR display that overlaps with the lead or merging vehicles. We tested the ARS with younger (18–30) and older (65–75) drivers in a high-fidelity driving simulator. Results showed that the ARS could significantly reduce collisions caused by hazard events such as sudden slowing of the lead vehicle or merging of vehicles from sides lanes. Consistent with previous results, older drivers, despite age-related decline in cognitive and motor abilities, could leverage their driving experience to avoid forward collisions with the lead vehicle as much as younger drivers. However, older drivers were poorer in avoiding collisions caused by sudden merging events than younger drivers. The ARS was found to be most useful in helping older adults to avoid collision caused by sudden hazard events, especially with the presence of a distraction task. The ARS was also more effective for older than younger drivers to encourage a safe driving distance with the lead vehicle. Interestingly, there seemed to be differential effects of the ARS on the general driving behavior of younger and older drivers. While older drivers in general became more careful and safer in how they drive with the ARS, younger drivers seemed to rely on the ARS to alert them to potential hazard events without adopting safer driving behavior.

We propose EDGE (An Easy Design Tool of Game Event for Rapid Game Development), with it game designers can make game events and effects without detailed programming skill. In the typical game design phase, the programming of game events is time consuming, non-productive, and burden to programmers; moreover, it is very difficult task for non-programmers. In this paper, we propose EDGE based game design process which clearly guarantees independence of game planning/design phase from the game programming phase. In the game design phase, game designer make events/effects without programming details. After verification of design process by EDGE preview, we can proceed to the game implementation phase, where we can use EDGE generated game source codes. We design and implement EDGE on OpenGL platform, applied EDGE on the development of two major genres of game contents, and the experimental results show that we can increase the productivity and the design maintenance.

Fingerprinting schemes use digital watermarks to determine originators of unauthorized/pirated copies. Multiple users may collude and collectively escape identification by creating an average or median of their individually watermarked copies. We present a scalable codebook generation scheme to increase the number of fingerprinted users. We extended the ACC (anti-collusion code) scheme using a Gaussian distributed random variable for medium attack robustness. We experimented with our scheme using human visual system based watermarking scheme, and the simulation results with standard test images show good collusion detection performance over average and median collusion attacks.