Scene categorization based on object bank
Xu Zhang, Min Jiang, Ziruo He · 2017
Scene Categorization is one of the most competitive topic in Robotics and computer vision. It classifies the given image based on the scene information. Object Bank is an object-level image representation for high-level visual recognition. Compared with low-level feature representations, Object Bank offers more rich description of images. In this paper, we proposed a Scene Categorization method based on Object Bank. This method improved the Object Bank by reducing the dimensions of the feature vectors extracted from the image and add low-level representation Locality-constrained Linear Coding. The experiments show that the classification efficiency and classification accuracy of the improved method is much higher.