Multi-class Graph Boosting with Subgraph Sharing for Object Recognition
Bang Zhang, Getian Ye, Yang Wang, Wei Wang, Jie Xu, Gunawan Herman, Yun Yang · 2010
In this paper, we propose a novel multi-class graph boosting algorithm to recognize different visual objects. The proposed method treats subgraph as feature to construct base classifier, and utilizes popular error correcting output code scheme to solve multi-class problem. Both factors, base classifier and error-correcting coding matrix are considered simultaneously. And subgragphs, which are shareable by different classes, are wisely used to improve the classification performance. The experimental results on multi-class object recognition show the effectiveness of the proposed algorithm.