Optimal View Selection Algorithm for 3D Object Based on Similarity Learning

Focusing on the problem that the existing optimal view measurement is difficult to measure different kinds of 3D objects,a new selection algorithm of optimal view for 3D object based on similarity learning is proposed in this paper.In this method,the optimal view samples for all kinds of 3D objects in the model library will be set up based on the use's knowledge firstly.Then through similarity learning,the optimal view of the input 3D object can be gotten.Here,the AdaBoost algorithm is used on the shape feature of input 3D object for similarity learning in order to get the optimal view sample of this object.Then the rendering views of the 3D object coming from different viewpoints are compared and analyzed with the optimal view sample on shape similarity matching.The rendering view with highest similarity will be regarded as the optimal view of the 3D Object.The experiments show that the optimal view selected can not only effectively close the user's knowledge,but also have good stability.