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Ivan Sipiran
Researcher at Pontifical Catholic University of Peru
Publications - 51
Citations - 1643
Ivan Sipiran is an academic researcher from Pontifical Catholic University of Peru. The author has contributed to research in topics: Computer science & Visual Word. The author has an hindex of 14, co-authored 43 publications receiving 1383 citations. Previous affiliations of Ivan Sipiran include University of Chile & University of Konstanz.
Papers
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Journal ArticleDOI
Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes
Ivan Sipiran,Benjamin Bustos +1 more
TL;DR: This paper proposes an adaptive technique to determine the neighborhood of a vertex, over which the Harris response on that vertex is calculated, and shows that Harris 3D outperforms the results obtained by recent effective techniques such as Heat Kernel Signatures.
Proceedings ArticleDOI
SHREC'11 track: shape retrieval on non-rigid 3D watertight meshes
Zhouhui Lian,Afzal Godil,Benjamin Bustos,Mohamed Daoudi,Jeroen Hermans,S. Kawamura,Yukinori Kurita,Guillaume Lavoué,Hien M. Nguyen,Ryutarou Ohbuchi,Yuki Ohkita,Yuya Ohishi,Fatih Porikli,Martin Reuter,Ivan Sipiran,Dirk Smeets,Paul Suetens,Hedi Tabia,Dirk Vandermeulen +18 more
TL;DR: This track is to measure and compare the performance of non-rigid 3D shape retrieval methods implemented by different participants around the world and their retrieval accuracies were evaluated using 6 commonly-utilized measures.
Journal ArticleDOI
A comparison of methods for non-rigid 3D shape retrieval
Zhouhui Lian,Afzal Godil,Benjamin Bustos,Mohamed Daoudi,Jeroen Hermans,S. Kawamura,Yukinori Kurita,Guillaume Lavoué,Hien M. Nguyen,Ryutarou Ohbuchi,Yuki Ohkita,Yuya Ohishi,Fatih Porikli,Martin Reuter,Ivan Sipiran,Dirk Smeets,Paul Suetens,Hedi Tabia,Dirk Vandermeulen +18 more
TL;DR: A new benchmark consisting of 600 non-rigid 3D watertight meshes, which are equally classified into 30 categories, is developed to carry out experiments for 11 different algorithms, whose retrieval accuracies are evaluated using six commonly utilized measures.
Proceedings ArticleDOI
SHREC 2011: robust feature detection and description benchmark
Edmond Boyer,Alexander M. Bronstein,Michael M. Bronstein,Benjamin Bustos,T. Darom,Radu Horaud,Ingrid Hotz,Yosi Keller,Johannes Keustermans,Artiom Kovnatsky,Roee Litman,Jan Reininghaus,Ivan Sipiran,Dirk Smeets,Paul Suetens,Dirk Vandermeulen,Andrei Zaharescu,Valentin Zobel +17 more
TL;DR: A benchmark that simulates the feature detection and description stages of feature-based shape retrieval algorithms under a wide variety of transformations is presented.
Proceedings ArticleDOI
A robust 3D interest points detector based on Harris operator
Ivan Sipiran,Benjamin Bustos +1 more
TL;DR: This paper proposes an adaptive technique to determine the neighborhood of a vertex, over which the Harris response on that vertex is calculated, and is robust to affine transformations and distortion transformation such as noise addition.