A Distributed Face Recognition Framework Based on Data Fusion
Zheng Zhang, Yan Qin Guo, Guozhi Song · International Journal of Database Theory and Application · 2014
To accomplish face recognition more efficiently, a distributed face recognition framework based on MB-LBP features and data fusion is presented in this paper.Firstly, four face regions are interactively marked and the Multi-scale Block Local Binary Patterns are extracted from these regions to achieve both locally and globally informative features.Secondly, a distributed framework is introduced to accelerate the recognition process, in which features of each single face region are utilized to perform face classification in parallel.The final decision is made by a kind of data fusion mechanism based on an artificial neural network (ANN) to make rational use of the confidence information got from the classification of each region.In experiment, the runtime and recognition performance of our system is compared with several other popular face recognition paradigms.The results indicate that the distributed framework presented in this paper can promote the efficiency of face recognition prominently while not losing accuracy in recognition performance.