Sketch Based Image Retrieval Based on Multi-layer Semantic Feature and Deep Convolutional Neural Network

In this paper,we studied the semantic features of the free-hand sketches in the research field of SBIR(sketch based image retrieval),and proposed a new approach to dig out the semantic property in sketches and improve the performance of sketches retrieval,which is based on multi-layer semantic feature learning and deep convolutional neural network.Our methods are demonstrated as follow:firstly,we put forward a new conception of multi-layer semantic feature descriptors;secondly,we constructed a corresponding multiple layers of deep convolutional neural network to learn the deep features of sketches;thirdly,we combined semantic features of different layers by the feature fusion algorithm to forming the final feature representations and to realize the high retrieval accuracy.The experiment on benchmark Flickr15k dataset proves the efficiency and accuracy of our proposed method.