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An novel stereo vision tracking method is proposed to implement an interactive Human Computer Interface(HCI). Firstly, a feature detection method is introduced to accurately obtain the location and orientation of the feature in an efficient way. Secondly, a searching method is carried out, which uses probability in the time, frequency or color space to optimize the searching strategy. Then the 3D information is retrieved by the calibration and triangulation process. Up to 5 degrees of freedom(DOFs) can be achieved from a single feature, compared with the other methods, including the coordinates in 3D space and the orientation information. Experiments show that the method is efficient and robust for the real time game interface. [ABSTRACT FROM AUTHOR]

The appeal of computer games may be enhanced by vision-based user inputs. The high speed and low cost requirements for near-term, mass-market game applications make system design challenging. In this paper we propose a vision based 3D racing car game controlling method, which analyzes two fists positions of the player in video stream from the camera to get the direction commands of the racing car. This paper especially focuses on the robust and real-time Bayesian network (BN) based multi-cue fusion fist tracking method. Firstly, a new strategy, which employs the latest work in face recognition, is used to create accurate color model of the fist automatically. Secondly, color cue and motion cue are used to generate the possible position of the fist. Then, the posterior probability of each possible position is evaluated by BN, which fuses color cue and appearance cue. Finally, the fist position is approximated by the hypothesis that maximizes a posterior. Based on the proposed control system, a racing car game, "Simulation Drive", has been developed by our group. Through the game an entirely new experience can be obtained by the player. [ABSTRACT FROM AUTHOR]

It is important for trusted intranets to focus on network security as a whole with dynamic and formalized analysis. The qualitative and current quantitative methods have difficulties to reach the requirements. After analyzing the attacking process, a Jackson network-based model with absorbing states is proposed, where the absorbing states mean the attacks succeed or fail. We compute the steady-state joint probability distribution of network nodes, the mean time of attack data spent in network, and the probabilities from the network entry node to absorbing states. According to the analysis of the above measures, we analyze the relationship between network security and performance. [ABSTRACT FROM AUTHOR]