Fisher encoding of differential fast point feature histograms for partial 3D object retrieval. (July 2016) - Savelonas, Michalis A.; Pratikakis, Ioannis; Sfikas, Konstantinos
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. Abstract : Highlights: First application of Fisher encoding in 3D object retrieval. The dFPFH extends FPFH, capturing more accurately local geometric transitions. The proposed similarity addresses partiality. The proposed method outperforms state-of-the-art in SHREC 2013 dataset. The proposed method outperforms state-of-the-art in cultural heritage datasets.