%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/07.11.00.37
%2 sid.inpe.br/sibgrapi/2016/07.11.00.37.55
%@doi 10.1109/SIBGRAPI.2016.068
%T Partial Similarity of 3D Shapes Using Cross Recurrence Plot
%D 2016
%A Nakanishi, Rafael Umino,
%A Ono, Jorge Piazentin,
%A Pagliosa, Paulo,
%A Nonato, Luis Gustavo,
%A Paiva, Afonso,
%@affiliation ICMC-USP
%@affiliation NYU
%@affiliation FACOM-UFMS
%@affiliation ICMC-USP
%@affiliation ICMC-USP
%E Aliaga, Daniel G.,
%E Davis, Larry S.,
%E Farias, Ricardo C.,
%E Fernandes, Leandro A. F.,
%E Gibson, Stuart J.,
%E Giraldi, Gilson A.,
%E Gois, João Paulo,
%E Maciel, Anderson,
%E Menotti, David,
%E Miranda, Paulo A. V.,
%E Musse, Soraia,
%E Namikawa, Laercio,
%E Pamplona, Mauricio,
%E Papa, João Paulo,
%E Santos, Jefersson dos,
%E Schwartz, William Robson,
%E Thomaz, Carlos E.,
%B Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)
%C São José dos Campos, SP, Brazil
%8 4-7 Oct. 2016
%I IEEE Computer Society´s Conference Publishing Services
%J Los Alamitos
%S Proceedings
%K Shape Retrieval, Cross Recurrence Plot, Heat Kernel Signature, Fiedler Vector, Time-Series Analysis, Geometry Processing.
%X This paper presents a novel 3D partial shape retrieval algorithm based on time-series analysis. Given a piece of a 3D shape, the proposed method encodes the shape descriptor given by the Heat Kernel Signature (HKS) as a time-series, where the time is considered an ordered sequence of vertices provided by the Fiedler vector. Finally, a similarity metric is created using a well-known tool in time-series analysis called Cross Recurrence Plot (CRP). The good performance of our method is also attested in a large collection of shape models.
%@language en
%3 PID4350307.pdf