Combining features for Chinese sign language recognition with Kinect

Geng, Lubo; Ma, Xin; Xue, Bingxia; Wu, Hanbo; Li, Yibin

doi:10.1109/icca.2014.6871127

Cited by 22 publications

(5 citation statements)

References 22 publications

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“…Perkembangan penelitian bahasa isyarat saat ini tentunya tidak hanya bergantung pada algoritma dan teknik pengenalan isyarat saja, akan tetapi para peneliti juga telah banyak mempresentasikan dari teknologi sensor yang ada. Sensor seperti smart glove [7], kamera digital [8] hingga kamera kinect [9] digunakan sebagai alat masukan (input device) bagi manusia untuk berinteraksi dengan sistem dan mengenali bahasa isyarat yang diberikan. Teknologi sensor lainnya yang terkini adalah Leap Motion Controller (LMC).…”

Section: Informal | 49 Issn : 2503 -250xunclassified

Penggunaan Dual Sensor Leap Motion Controller untuk Sistem Isyarat Bahasa Indonesia (SIBI)

Nugraha

Murti²,

Khotimah³

2019

INFORMAL

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Bahasa isyarat adalah bahasa yang dibentuk dengan kombinasi gerakan jari, tangan, tubuh serta ekspresi wajah yang digunakan oleh para penyandang disabilitas seperti tunarungu dan tunawicara. Salah satu pengenalan bahasa isyarat tersebut adalah pengenalan dengan menggunakan teknologi sensor Leap Motion Controller (LMC). Akan tetapi pada penerapannya, sensor LMC tidak selalu dapat mengenali semua jari dengan baik. Hal ini dikarenakan pembentukan dari bahasa isyarat yang saling bersentuhan antar jari, jari yang dilipat, tersembunyi ataupun terhalang oleh jari lainnya. Sehingga pada penelitian ini diusulkan penggunaan dual sensor LMC yang bertujuan untuk mencegah dan meminimalisir adanya kesalahan dalam mengenal bahasa isyarat dari jari yang dibentuk. Tahapan proses yang dilakukan adalah mendesain tata letak sensor LMC dan mengkombinasikan data fitur dari masing-masing sensor LMC baik yang bersifat statis dan dinamis yang kemudian diklasifikasikan menggunakan metode L-GCNN. Dari hasil pengujian yang dilakukan, penggunaan dual sensor LMC ini dapat mengenal isyarat SIBI yang diberikan. Skema yang terbaik adalah dengan mengacu pada tata letak multi sensor yang saling berhadapan membentuk sudut 120 derajat dengan tingkat akurasi sebesar 86,42%, dengan rata-rata akurasi dari keseluruhan skenario sebesar 84,36%. Adanya desain tata letak sensor LMC dan kombinasi penggabungan data fitur masing-masing sensor dapat meningkatkan akurasi pengenalan dengan rata-rata peningkatan mencapai 5,35%.

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Section: Informal | 49 Issn : 2503 -250xunclassified

Penggunaan Dual Sensor Leap Motion Controller untuk Sistem Isyarat Bahasa Indonesia (SIBI)

Nugraha

Murti²,

Khotimah³

2019

INFORMAL

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“…43 Their experiments show that by combining the features, the recognition accuracy is improved. Furthermore, ELM, which is a variation of neural networks, is shown to perform better than SVM on recognition accuracy.…”

Section: Speech and Sign Language Recognitionmentioning

confidence: 99%

A Survey of Applications and Human Motion Recognition with Microsoft Kinect

Lun

Zhao

2015

Int. J. Patt. Recogn. Artif. Intell.

281

109

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Microsoft Kinect, a low-cost motion sensing device, enables users to interact with computers or game consoles naturally through gestures and spoken commands without any other peripheral equipment. As such, it has commanded intense interests in research and development on the Kinect technology. In this paper, we present, a comprehensive survey on Kinect applications, and the latest research and development on motion recognition using data captured by the Kinect sensor. On the applications front, we review the applications of the Kinect technology in a variety of areas, including healthcare, education and performing arts, robotics, sign language recognition, retail services, workplace safety training, as well as 3D reconstructions. On the technology front, we provide an overview of the main features of both versions of the Kinect sensor together with the depth sensing technologies used, and review literatures on human motion recognition techniques used in Kinect applications. We provide a classi¯cation of motion recognition techniques to highlight the di®erent approaches used in human motion recognition. Furthermore, we compile a list of publicly available Kinect datasets. These datasets are valuable resources for researchers to investigate better methods for human motion recognition and lowerlevel computer vision tasks such as segmentation, object detection and human pose estimation.

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“…Around the world, different approaches and communication methods in the education of D/HH students exist (Deaf, 2014). SL is the main language used to communicate between D/HH students and teachers in the classroom (Geng et al, 2014). Figure 2 shows the literacy learning flow of D/HH students.…”

Section: D/hh Educationmentioning

confidence: 99%

Literacy Sign Language Application Using Visual Phonics

Abdulghafoor

Ahmad

Huang

2015

International Journal of Web-Based Learning and Teaching Technologies

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Literacy is the ability to read and write. Being able to read and write is an important skill in modern society. Deaf and hard of hearing (D/HH) students' literacy achievement has been reported as lower than that of hearing students. This research focuses on the literacy skills of D/HH students, aiming to determine their reading/writing skills and propose a theoretical framework that can enhance and improve these skills. This paper provides an introduction on D/HH education, including tools and challenges, an analysis of existing literature related to D/HH education applications, and sign language (SL) applications. The advances that are needed to further improve the effectiveness and efficiency of present reading and writing teaching techniques are further discussed, and a comparative survey conducted in this area is provided. The study explores the significance of Visual Phonics for D/HH as a motivating force for research in reading and writing taxonomies. The objective of this study is to propose a theoretical framework that can enhance and improve D/HH reading and writing skills.

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Combining features for Chinese sign language recognition with Kinect

Cited by 22 publications

References 22 publications

Penggunaan Dual Sensor Leap Motion Controller untuk Sistem Isyarat Bahasa Indonesia (SIBI)

Penggunaan Dual Sensor Leap Motion Controller untuk Sistem Isyarat Bahasa Indonesia (SIBI)

A Survey of Applications and Human Motion Recognition with Microsoft Kinect

Literacy Sign Language Application Using Visual Phonics

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