Papers by Author: Zhi Jie Li

Abstract: This paper presents an automatic approach for facial expression deformation. In order to guarantee the expression deformation is dealt with high quality and conveniently, the approach uses two key technologies: the PSO detection and the affine transformation. The simulation results show that this method can produce natural smile expression, without marking the spots manually, especially works well for some shy smile expressions.

Abstract: This paper presents a new method using PSO for face detection, which does not utilize training samples. The method is based on the edge density of the image. In the preprocessing stage a face is approximated to a rectangle. Then PSO algorithm is applied to search for the best rectangle region. The rectangle area with best fitness value will be detected as the face region. Simulation results show that this PSO-based method is convergent and effective, especially for the case of images with the non complex background.

Abstract: The present thesis puts forward a hierarchical P2P model: self-adaptive P2P model of two-level. Super peers compose a self-adaptive DHT network on the top layer, and lower ordinary peers take super peer in the same group as their center server to form a cluster. Data are stored in ordinary peers and super peers hold indices of data and answer for request from ordinary peers. When super peer join or leave, it does not maintain consistency of entire network’s logic topology but only update routing table of its predecessor and successor, besides, super peers update their routing table cache when they transmit messages. The ordinary peers keep backup of super peer for system restore when super peer fails. System can optimize network structure by select peers with high capacity to be super peer and restrict amount of peers in each group.

Abstract: This paper presents a generating algorithm at pixel level for parametric curve. The parallel particle sub-swarm optimization is used to search the optimal step of curve in forward. Large amount of repeated computing for points are avoided and the result is precise enough. Simulation results show that the parallel method based on particle sub-swarm can be used for searching the optimal step of parametric curve with any degree quickly. At the same time, compared with other methods, this algorithm produces the maximum step efficiently. Since there is no restriction on control point position and curve degree, the algorithm can be extended easily to other parametric curves besides Bézier curves.