3D object retrieval based on Bayesian networks lightfield descriptor and feedback learning

A new 3D object retrieval approach is proposed based on a novel Bayesian networks lightfield descriptor (BLD). To overcome the disadvantages of the existing 3D object retrieval methods, firstly, we explore Bayesian network for building a new lightfield descriptor, 3D object is put into lightfield, and multi-views information can be obtained along a sphere, and then features of images can be extracted out. The BLD of 3D object would be got according to feature sequences based on Bayesian network learning algorithm. Secondly, 3D object is retrieved based on graph model measurement and relevant feedback learning. Beneficial from the statistical learning and graph model optimization, proposed BLD is robustness as compared to the existing methods. Experimental results demonstrate that proposed approach is with better performance than the existing methods.