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Crowd formation of aesthetic transformation is considered to have extremely high artistic value and is widely applied in large-scale performances. In this paper, a spatio-temporal hierarchical model that parts the crowd formation transform into multiple granularities is proposed. Its core idea is to add spatio-temporal constraints created by directors into transformation process after multi-level division. In this model, average hash value and energy optimization are used to achieve reasonable crowd formation arrangement, while smooth and collision-free formation transformations are presented by constrained region growth and Kuhn-Munkres algorithm. We have also proposed a framework to achieve the generation of visually pleasing crowd formation transform performance based on the constraints. Besides, a virtual crowd formation transformation simulation was built to verify the effect of the proposed model. Through simulation experiments and comparisons, it was demonstrated that this hierarchical model can generate aesthetic crowd formation transformation with a satisfactory process.

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Abstract-This paper addresses the problem of group path planning while maintaining group coherence and persistence. Group coherence ensures that a group minimizes both longitudinal and lateral dispersion, and is achieved with the introduction of a deformation penalty to the cost formulation. When the deformation penalty is significantly high, a group may split and later merge. Group persistence is modeled by introducing split and merge actions in the action space, and adding a split penalty to the cost measure. We formulate the problem domain (state, action space, and cost formulation), present our path planning approach for coherent and persistent groups, and provide empirical results demonstrating the capabilities of our method on a variety of challenging scenarios.

IEEE 802.11 has evolved from 802.11a/b/g/n to 802.11ac to meet rapidly increasing data rate requirements in WLANs. One important technique adopted in 802.11ac is the channel bonding (CB) scheme that combines multiple 20MHz channels for a single transmission in 5GHz band. In order to effectively access channel after a series of contention operations, 802.11ac specifies two different CB operations: Dynamic Channel Bonding (DCB) and Static Channel Bonding (SCB). This paper proposes an optimal channel allocation algorithm to achieve maximal throughputs in DCB WLANs. Specifically, we first adopt a continuous-time Markov Chain (CTMC) model to analyze the equilibrium throughputs. Based on the throughput analysis, we then construct an integer nonlinear programming (INLP) model with the target of maximizing system throughput. By solving the INLP model, we then propose an optimal channel allocation algorithm based on the Branch-and-Bound Method (BBM). It turns out that the maximal throughput performance can be achieved under the channel allocation scheme with the least overlapped channels among WLANs. Simulations show that the proposed algorithm can achieve the maximal system throughput under various network settings. We believe that our analysis on the optimal channel allocation schemes brings new insights into the design and optimization of future WLANs, especially for those adopting channel bonding technique.