Indoor Scene Classification Based on the Bag-of-Words Model of Local Feature Information Gain

摘要

For the problem of Indoor Home Scene Classification, this paper proposes the BOW Model of Local Feature Information Gain. The experimental results show that not only the performance is improved but also the computation is reduced. Consequently this method out performs the state-of-the-art approach.