The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kertas kerja ini mencadangkan kaedah untuk mendapatkan semula data pergerakan manusia dengan peraturan perolehan ringkas berdasarkan ciri spatio-temporal penampilan gerakan. Kaedah kami mula-mula menukar klip gerakan ke dalam bentuk bahasa klausa yang mewakili hubungan geometri antara bahagian badan dan hubungan temporalnya. Peraturan pengambilan kemudian dipelajari daripada set contoh terperingkat secara manual menggunakan pengaturcaraan logik induktif (ILP). ILP secara automatik menemui peraturan penting dalam bentuk klausa yang sama dengan prosedur ujian hipotesis yang ditentukan pengguna. Semua gerakan diindeks menggunakan bahasa klausa ini dan klip yang diingini diambil dengan padanan berikutnya menggunakan peraturan. Pengambilan semula berasaskan peraturan sedemikian menawarkan prestasi yang munasabah dan peraturan itu boleh disunting secara intuitif dalam bentuk bahasa yang sama. Akibatnya, kaedah kami membolehkan carian yang cekap dan fleksibel daripada set data yang besar dengan bahasa pertanyaan mudah.
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Salinan
Tomohiko MUKAI, Ken-ichi WAKISAKA, Shigeru KURIYAMA, "Generating Concise Rules for Human Motion Retrieval" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 6, pp. 1636-1643, June 2010, doi: 10.1587/transinf.E93.D.1636.
Abstract: This paper proposes a method for retrieving human motion data with concise retrieval rules based on the spatio-temporal features of motion appearance. Our method first converts motion clip into a form of clausal language that represents geometrical relations between body parts and their temporal relationship. A retrieval rule is then learned from the set of manually classified examples using inductive logic programming (ILP). ILP automatically discovers the essential rule in the same clausal form with a user-defined hypothesis-testing procedure. All motions are indexed using this clausal language, and the desired clips are retrieved by subsequence matching using the rule. Such rule-based retrieval offers reasonable performance and the rule can be intuitively edited in the same language form. Consequently, our method enables efficient and flexible search from a large dataset with simple query language.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.1636/_p
Salinan
@ARTICLE{e93-d_6_1636,
author={Tomohiko MUKAI, Ken-ichi WAKISAKA, Shigeru KURIYAMA, },
journal={IEICE TRANSACTIONS on Information},
title={Generating Concise Rules for Human Motion Retrieval},
year={2010},
volume={E93-D},
number={6},
pages={1636-1643},
abstract={This paper proposes a method for retrieving human motion data with concise retrieval rules based on the spatio-temporal features of motion appearance. Our method first converts motion clip into a form of clausal language that represents geometrical relations between body parts and their temporal relationship. A retrieval rule is then learned from the set of manually classified examples using inductive logic programming (ILP). ILP automatically discovers the essential rule in the same clausal form with a user-defined hypothesis-testing procedure. All motions are indexed using this clausal language, and the desired clips are retrieved by subsequence matching using the rule. Such rule-based retrieval offers reasonable performance and the rule can be intuitively edited in the same language form. Consequently, our method enables efficient and flexible search from a large dataset with simple query language.},
keywords={},
doi={10.1587/transinf.E93.D.1636},
ISSN={1745-1361},
month={June},}
Salinan
TY - JOUR
TI - Generating Concise Rules for Human Motion Retrieval
T2 - IEICE TRANSACTIONS on Information
SP - 1636
EP - 1643
AU - Tomohiko MUKAI
AU - Ken-ichi WAKISAKA
AU - Shigeru KURIYAMA
PY - 2010
DO - 10.1587/transinf.E93.D.1636
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2010
AB - This paper proposes a method for retrieving human motion data with concise retrieval rules based on the spatio-temporal features of motion appearance. Our method first converts motion clip into a form of clausal language that represents geometrical relations between body parts and their temporal relationship. A retrieval rule is then learned from the set of manually classified examples using inductive logic programming (ILP). ILP automatically discovers the essential rule in the same clausal form with a user-defined hypothesis-testing procedure. All motions are indexed using this clausal language, and the desired clips are retrieved by subsequence matching using the rule. Such rule-based retrieval offers reasonable performance and the rule can be intuitively edited in the same language form. Consequently, our method enables efficient and flexible search from a large dataset with simple query language.
ER -