DEEP-CSSR: Scene classification using category-specific salient region with deep features
Mengshi Qi, Yunhong Wang · 2016
Researches in neuroscience and biological vision have shown that the bio-inspired methods have excellent recognition performance, such as the salient detection, artificial neural network and the ganglion cell inspired image feature. In this paper, we introduce a novel framework towards scene classification using category-specific salient region(CSSR) with deep CNN features, called Deep-CSSR. Firstly, by using the salient region detection algorithm, we extract a set of image patches which contain the salient regions. Also we apply DERF, a novel bio-inspired image descriptor, to represent the salient patches and clustering all of them to remove the outliers. Then we learn the CSSR filters and construct the CSSR representation. Further more, we do scene image classification using CSSR representation concatenate with the deep CNN features extracted from the whole images. By using this new pipeline, we obtain better results than recent methods over MIT Indoor 67 and Sun397 databases.