Fisher Encoding of Differential Fast Point Feature Histograms for Partial 3D Object Retrieval
|Title||Fisher Encoding of Differential Fast Point Feature Histograms for Partial 3D Object Retrieval|
|Publication Type||Journal Article|
|Year of Publication||2016|
|Authors||Savelonas, MA, Pratikakis, I, Sfikas, K|
Abstract Partial 3D object retrieval has attracted intense research efforts due to its potential for a wide range of applications, such as 3D object repair and predictive digitization. This work introduces a partial 3D object retrieval method, applicable on both point clouds and structured 3D models, which is based on a shape matching scheme combining local shape descriptors with their Fisher encodings. Experiments on the SHREC 2013 large-scale benchmark dataset for partial object retrieval, as well as on the publicly available Hampson pottery dataset, demonstrate that the proposed method outperforms seven recently evaluated partial retrieval methods.