Indonesian language sign system (SIBI) recognition using threshold conditional random fields

I. Gusti Bagus Hadi Widhinugraha; Erdefi Rakun

doi:10.1145/3373509.3373591

Indonesian language sign system (SIBI) recognition using threshold conditional random fields

I. Gusti Bagus Hadi Widhinugraha, Erdefi Rakun

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

The Sign System for Indonesian Language or Sistem Isyarat Bahasa Indonesia? (SIBI) is a sign language system that is used to represent Indonesian language. The referred sign language is a systematic movement of fingers and hands to represent a vocabulary. This paper utilizes the Threshold Conditional Random Field (TCRF) model to identify gesture and nongesture automatically. The generated model is an early model to establish a SIBI translation system automatically. Data that were utilized in this research are Skeleton, Image, and Skeleton Image Combination. Data were processed by implementing TCRF algorithm to provide gesture and non-gesture labels automatically. Several experiments had pointed to the highest accuracy up to 81,5% by using skeletal data as an input in TCRF.

Original language	English
Title of host publication	ICCPR 2019 - 2019 8th International Conference on Computing and Pattern Recognition
Publisher	Association for Computing Machinery
Pages	380-384
Number of pages	5
ISBN (Electronic)	9781450376570
DOIs	https://doi.org/10.1145/3373509.3373591
Publication status	Published - 23 Oct 2019
Event	8th International Conference on Computing and Pattern Recognition, ICCPR 2019 - Beijing, China Duration: 23 Oct 2019 → 25 Oct 2019

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	8th International Conference on Computing and Pattern Recognition, ICCPR 2019
Country/Territory	China
City	Beijing
Period	23/10/19 → 25/10/19

Keywords

Conditional random field
SIBI
Sign language recognition
Threshold

Access to Document

10.1145/3373509.3373591

Cite this

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title = "Indonesian language sign system (SIBI) recognition using threshold conditional random fields",

abstract = "The Sign System for Indonesian Language or Sistem Isyarat Bahasa Indonesia? (SIBI) is a sign language system that is used to represent Indonesian language. The referred sign language is a systematic movement of fingers and hands to represent a vocabulary. This paper utilizes the Threshold Conditional Random Field (TCRF) model to identify gesture and nongesture automatically. The generated model is an early model to establish a SIBI translation system automatically. Data that were utilized in this research are Skeleton, Image, and Skeleton Image Combination. Data were processed by implementing TCRF algorithm to provide gesture and non-gesture labels automatically. Several experiments had pointed to the highest accuracy up to 81,5% by using skeletal data as an input in TCRF.",

keywords = "Conditional random field, SIBI, Sign language recognition, Threshold",

author = "Widhinugraha, {I. Gusti Bagus Hadi} and Erdefi Rakun",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 8th International Conference on Computing and Pattern Recognition, ICCPR 2019 ; Conference date: 23-10-2019 Through 25-10-2019",

year = "2019",

month = oct,

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doi = "10.1145/3373509.3373591",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

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Widhinugraha, IGBH & Rakun, E 2019, Indonesian language sign system (SIBI) recognition using threshold conditional random fields. in ICCPR 2019 - 2019 8th International Conference on Computing and Pattern Recognition. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 380-384, 8th International Conference on Computing and Pattern Recognition, ICCPR 2019, Beijing, China, 23/10/19. https://doi.org/10.1145/3373509.3373591

Indonesian language sign system (SIBI) recognition using threshold conditional random fields. / Widhinugraha, I. Gusti Bagus Hadi; Rakun, Erdefi.
ICCPR 2019 - 2019 8th International Conference on Computing and Pattern Recognition. Association for Computing Machinery, 2019. p. 380-384 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Indonesian language sign system (SIBI) recognition using threshold conditional random fields

AU - Widhinugraha, I. Gusti Bagus Hadi

AU - Rakun, Erdefi

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N2 - The Sign System for Indonesian Language or Sistem Isyarat Bahasa Indonesia? (SIBI) is a sign language system that is used to represent Indonesian language. The referred sign language is a systematic movement of fingers and hands to represent a vocabulary. This paper utilizes the Threshold Conditional Random Field (TCRF) model to identify gesture and nongesture automatically. The generated model is an early model to establish a SIBI translation system automatically. Data that were utilized in this research are Skeleton, Image, and Skeleton Image Combination. Data were processed by implementing TCRF algorithm to provide gesture and non-gesture labels automatically. Several experiments had pointed to the highest accuracy up to 81,5% by using skeletal data as an input in TCRF.

AB - The Sign System for Indonesian Language or Sistem Isyarat Bahasa Indonesia? (SIBI) is a sign language system that is used to represent Indonesian language. The referred sign language is a systematic movement of fingers and hands to represent a vocabulary. This paper utilizes the Threshold Conditional Random Field (TCRF) model to identify gesture and nongesture automatically. The generated model is an early model to establish a SIBI translation system automatically. Data that were utilized in this research are Skeleton, Image, and Skeleton Image Combination. Data were processed by implementing TCRF algorithm to provide gesture and non-gesture labels automatically. Several experiments had pointed to the highest accuracy up to 81,5% by using skeletal data as an input in TCRF.

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KW - Sign language recognition

KW - Threshold

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M3 - Conference contribution

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T3 - ACM International Conference Proceeding Series

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BT - ICCPR 2019 - 2019 8th International Conference on Computing and Pattern Recognition

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Y2 - 23 October 2019 through 25 October 2019

ER -

Indonesian language sign system (SIBI) recognition using threshold conditional random fields

Abstract

Publication series

Conference

Keywords

Access to Document

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