REBOR: A new sketch-based 3d object retrieval framework using retina inspired features

With the rapid development of data science and modeling engineering, the capacity of cyberspace has significantly expanded which enables the online storage of increasing number of 3D models. Hence, the development of effective and efficient approaches to search 3D models is becoming increasingly important and urgent. In this paper, we propose a new sketch-based 3D retrieval framework named REBOR under the inspiration of retina which is not only consistent with human perception sensitivity but also simplifies the requirement of retrieval query by enabling hand-drawn sketch. The feature extraction process incorporates human visual system by simulating the ganglion perceptive mechanism in retina. Support Vector Machine is used to classify the query sketches and is further optimized by means of an global optimization algorithm so as to acquire optimal results automatically. Experiments are done on the database generated by ourselves with 15 categories of 3D objects, and the results indicate the effectiveness of REBOR in terms of retrieval accuracy.