Real-time grasp type recognition using leap motion controller

Yuanyuan Zou; Honghai Liu; Jilong Zhang

doi:10.1007/978-3-030-27535-8_42

Real-time grasp type recognition using leap motion controller

Yuanyuan Zou, Honghai Liu, Jilong Zhang

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

278 Downloads (Pure)

Abstract

The recognition of grasp type is essential for a more detailed analysis of human action. In this paper, we propose a novel method for real-time grasp type recognition using Leap motion controller (LMC). Our proposal is based on the tracking data provided by the LMC sensor and a series of feature descriptors are introduced and extracted from LMC data. Combining the feature descriptors of relative positions of thumb, finger joint angles and finger directions lead to the best representation of the arrangement of the fingers. And then the grasp type classification can be achieved by using a SVM classifier. An experimental study of our approach is addressed and we show that recognition rate could be improved. The current implementation is also can satisfy the real-time requirements.

Original language	English
Title of host publication	Intelligent Robotics and Applications
Subtitle of host publication	12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part III
Editors	Haibin Yu, Jinguo Liu, Lianquing Liu, Zhaojie Liu, Dalin Zhou
Publisher	Springer
Chapter	42
Pages	472-480
Number of pages	9
ISBN (Electronic)	978-3-030-27535-8
ISBN (Print)	978-3-030-27534-1
DOIs	https://doi.org/10.1007/978-3-030-27535-8_42
Publication status	Published - 2 Aug 2019
Event	12th International Conference on Intelligent Robotics and Applications - Shenyang, China Duration: 8 Aug 2019 → 11 Aug 2019

Publication series

Name	Lecture Notes in Computer Science
Publisher	Sprnger
Volume	11742
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer
Volume	11742
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Intelligent Robotics and Applications
Abbreviated title	ICIRA 2019
Country/Territory	China
City	Shenyang
Period	8/08/19 → 11/08/19

Keywords

grasp type recognition
feature representation
SVM
leap motion controller

Access to Document

10.1007/978-3-030-27535-8_42

Zou_Real-time Grasp Type Recognition_ICIRA2019_154_final_v4
This is a post-peer-review, pre-copyedit version of an article published in Intelligent Robotics and Applications. ICIRA 2019. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-27535-8_42.
Accepted author manuscript (Post-print), 378 KB

Cite this

Zou, Y., Liu, H., & Zhang, J. (2019). Real-time grasp type recognition using leap motion controller. In H. Yu, J. Liu, L. Liu, Z. Liu, & D. Zhou (Eds.), Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part III (pp. 472-480). (Lecture Notes in Computer Science; Vol. 11742), (Lecture Notes in Artificial Intelligence; Vol. 11742). Springer. https://doi.org/10.1007/978-3-030-27535-8_42

Zou, Yuanyuan ; Liu, Honghai ; Zhang, Jilong. / Real-time grasp type recognition using leap motion controller. Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part III. editor / Haibin Yu ; Jinguo Liu ; Lianquing Liu ; Zhaojie Liu ; Dalin Zhou. Springer, 2019. pp. 472-480 (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence).

@inproceedings{e058f4e2350247febce226d31bfa2f37,

title = "Real-time grasp type recognition using leap motion controller",

abstract = "The recognition of grasp type is essential for a more detailed analysis of human action. In this paper, we propose a novel method for real-time grasp type recognition using Leap motion controller (LMC). Our proposal is based on the tracking data provided by the LMC sensor and a series of feature descriptors are introduced and extracted from LMC data. Combining the feature descriptors of relative positions of thumb, finger joint angles and finger directions lead to the best representation of the arrangement of the fingers. And then the grasp type classification can be achieved by using a SVM classifier. An experimental study of our approach is addressed and we show that recognition rate could be improved. The current implementation is also can satisfy the real-time requirements.",

keywords = "grasp type recognition, feature representation, SVM, leap motion controller",

author = "Yuanyuan Zou and Honghai Liu and Jilong Zhang",

year = "2019",

month = aug,

day = "2",

doi = "10.1007/978-3-030-27535-8_42",

language = "English",

isbn = "978-3-030-27534-1",

series = "Lecture Notes in Computer Science",

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editor = "Haibin Yu and Jinguo Liu and Lianquing Liu and Zhaojie Liu and Dalin Zhou",

booktitle = "Intelligent Robotics and Applications",

note = "12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 ; Conference date: 08-08-2019 Through 11-08-2019",

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Zou, Y, Liu, H & Zhang, J 2019, Real-time grasp type recognition using leap motion controller. in H Yu, J Liu, L Liu, Z Liu & D Zhou (eds), Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part III. Lecture Notes in Computer Science, vol. 11742, Lecture Notes in Artificial Intelligence, vol. 11742, Springer, pp. 472-480, 12th International Conference on Intelligent Robotics and Applications, Shenyang, China, 8/08/19. https://doi.org/10.1007/978-3-030-27535-8_42

Real-time grasp type recognition using leap motion controller. / Zou, Yuanyuan; Liu, Honghai; Zhang, Jilong.
Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part III. ed. / Haibin Yu; Jinguo Liu; Lianquing Liu; Zhaojie Liu; Dalin Zhou. Springer, 2019. p. 472-480 (Lecture Notes in Computer Science; Vol. 11742), (Lecture Notes in Artificial Intelligence; Vol. 11742).

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

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AU - Liu, Honghai

AU - Zhang, Jilong

PY - 2019/8/2

Y1 - 2019/8/2

N2 - The recognition of grasp type is essential for a more detailed analysis of human action. In this paper, we propose a novel method for real-time grasp type recognition using Leap motion controller (LMC). Our proposal is based on the tracking data provided by the LMC sensor and a series of feature descriptors are introduced and extracted from LMC data. Combining the feature descriptors of relative positions of thumb, finger joint angles and finger directions lead to the best representation of the arrangement of the fingers. And then the grasp type classification can be achieved by using a SVM classifier. An experimental study of our approach is addressed and we show that recognition rate could be improved. The current implementation is also can satisfy the real-time requirements.

AB - The recognition of grasp type is essential for a more detailed analysis of human action. In this paper, we propose a novel method for real-time grasp type recognition using Leap motion controller (LMC). Our proposal is based on the tracking data provided by the LMC sensor and a series of feature descriptors are introduced and extracted from LMC data. Combining the feature descriptors of relative positions of thumb, finger joint angles and finger directions lead to the best representation of the arrangement of the fingers. And then the grasp type classification can be achieved by using a SVM classifier. An experimental study of our approach is addressed and we show that recognition rate could be improved. The current implementation is also can satisfy the real-time requirements.

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KW - feature representation

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KW - leap motion controller

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DO - 10.1007/978-3-030-27535-8_42

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Y2 - 8 August 2019 through 11 August 2019

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Zou Y, Liu H, Zhang J. Real-time grasp type recognition using leap motion controller. In Yu H, Liu J, Liu L, Liu Z, Zhou D, editors, Intelligent Robotics and Applications: 12th International Conference, ICIRA 2019, Shenyang, China, August 8–11, 2019, Proceedings, Part III. Springer. 2019. p. 472-480. (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). doi: 10.1007/978-3-030-27535-8_42

Real-time grasp type recognition using leap motion controller

Abstract

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Keywords

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