A Fast Clustering Approach for Effectively Searching Person Specific Image

摘要

Person-specific image searching and retrieval is an important issue in several areas, including biometrics, robot vision, human-computer interfaces and surveillance. A wildly accepted retrieval methods are always relevant with either large-scale features description or complicated classifiers design. In this paper a system using an image clustering method is presented, which enables fast approximate search based on person face image. First, for face detection, both skin color segmentation strategy and the AdaBoost algorithm have been employed. In clustering, different image streams have been achieved in unsupervised manner where no prior knowledge about the input sequence is required. The proposed system applied to a variety of image datasets with satisfactory performance was demonstrated by the experimental results. The proposed method is also highly efficient, since most computations can be out-sourced to the GPU and competitive with other systems presented recently in the literatures.