Human action classification in basketball: A single inertial sensor based framework

Xiangyi Meng; Rui Xu; Xuantong Chen; Lingxiang Zheng; Ao Peng; Hai Lu; Haibin Shi; Biyu Tang; Huiru Zheng

doi:10.1007/978-981-10-7398-4_16

Human action classification in basketball: A single inertial sensor based framework

Xiangyi Meng
, Rui Xu
, Xuantong Chen
, Lingxiang Zheng
, Ao Peng
, Hai Lu
, Haibin Shi
, Biyu Tang
, Huiru Zheng

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

1 Citation (Scopus)

Abstract

Human Action Recognition is becoming more and more important in many fields, especially in sports. However, conventional algorithm are almost camera-based methods, which make it cumbersome and expensive. As the wearable inertial sensor has developed a lot, in this paper, we present a novel human action classification algorithm using in basketball, based on a single inertial sensor, which is a application of multi-label classification. We performed experiment on real world datasets. The AUPRC, AUROC and confusion matrix of our results demonstrated that our novel basketball motion recognizer have a great performance.

Original language	English
Title of host publication	Frontier Computing - Theory, Technologies and Applications FC 2017
Publisher	Springer
Pages	152-161
Number of pages	10
Volume	464
ISBN (Print)	9789811073977
DOIs	https://doi.org/10.1007/978-981-10-7398-4_16
Publication status	Published (in print/issue) - 19 Apr 2018
Event	6th International Conference on Frontier Computing, FC 2017 - Osaka, Japan Duration: 12 Jul 2017 → 14 Jul 2017

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	464
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	6th International Conference on Frontier Computing, FC 2017
Country/Territory	Japan
City	Osaka
Period	12/07/17 → 14/07/17

Funding

Acknowledgments. This work is supported by Student’s Platform for Innovation and Entrepreneurship Training Program, Xiamen University (2016Y1123), and 2016 Google Student Innovation Project (64008066).

Keywords

Basketball motion
Feature extraction
Human action recognition
Multi-label classification
Single inertial sensor
Support vector machine

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10.1007/978-981-10-7398-4_16

Cite this

Meng, X., Xu, R., Chen, X., Zheng, L., Peng, A., Lu, H., Shi, H., Tang, B., & Zheng, H. (2018). Human action classification in basketball: A single inertial sensor based framework. In Frontier Computing - Theory, Technologies and Applications FC 2017 (Vol. 464, pp. 152-161). (Lecture Notes in Electrical Engineering; Vol. 464). Springer. https://doi.org/10.1007/978-981-10-7398-4_16

@inproceedings{2505d2fd49134a63a44187d34a4747d7,

title = "Human action classification in basketball: A single inertial sensor based framework",

abstract = "Human Action Recognition is becoming more and more important in many fields, especially in sports. However, conventional algorithm are almost camera-based methods, which make it cumbersome and expensive. As the wearable inertial sensor has developed a lot, in this paper, we present a novel human action classification algorithm using in basketball, based on a single inertial sensor, which is a application of multi-label classification. We performed experiment on real world datasets. The AUPRC, AUROC and confusion matrix of our results demonstrated that our novel basketball motion recognizer have a great performance.",

keywords = "Basketball motion, Feature extraction, Human action recognition, Multi-label classification, Single inertial sensor, Support vector machine",

author = "Xiangyi Meng and Rui Xu and Xuantong Chen and Lingxiang Zheng and Ao Peng and Hai Lu and Haibin Shi and Biyu Tang and Huiru Zheng",

year = "2018",

month = apr,

day = "19",

doi = "10.1007/978-981-10-7398-4\_16",

language = "English",

isbn = "9789811073977",

volume = "464",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer",

pages = "152--161",

booktitle = "Frontier Computing - Theory, Technologies and Applications FC 2017",

address = "Switzerland",

note = "6th International Conference on Frontier Computing, FC 2017 ; Conference date: 12-07-2017 Through 14-07-2017",

}

Meng, X, Xu, R, Chen, X, Zheng, L, Peng, A, Lu, H, Shi, H, Tang, B & Zheng, H 2018, Human action classification in basketball: A single inertial sensor based framework. in Frontier Computing - Theory, Technologies and Applications FC 2017. vol. 464, Lecture Notes in Electrical Engineering, vol. 464, Springer, pp. 152-161, 6th International Conference on Frontier Computing, FC 2017, Osaka, Japan, 12/07/17. https://doi.org/10.1007/978-981-10-7398-4_16

Human action classification in basketball: A single inertial sensor based framework. / Meng, Xiangyi; Xu, Rui; Chen, Xuantong et al.
Frontier Computing - Theory, Technologies and Applications FC 2017. Vol. 464 Springer, 2018. p. 152-161 (Lecture Notes in Electrical Engineering; Vol. 464).

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

TY - GEN

T1 - Human action classification in basketball

T2 - 6th International Conference on Frontier Computing, FC 2017

AU - Meng, Xiangyi

AU - Xu, Rui

AU - Chen, Xuantong

AU - Zheng, Lingxiang

AU - Peng, Ao

AU - Lu, Hai

AU - Shi, Haibin

AU - Tang, Biyu

AU - Zheng, Huiru

PY - 2018/4/19

Y1 - 2018/4/19

N2 - Human Action Recognition is becoming more and more important in many fields, especially in sports. However, conventional algorithm are almost camera-based methods, which make it cumbersome and expensive. As the wearable inertial sensor has developed a lot, in this paper, we present a novel human action classification algorithm using in basketball, based on a single inertial sensor, which is a application of multi-label classification. We performed experiment on real world datasets. The AUPRC, AUROC and confusion matrix of our results demonstrated that our novel basketball motion recognizer have a great performance.

AB - Human Action Recognition is becoming more and more important in many fields, especially in sports. However, conventional algorithm are almost camera-based methods, which make it cumbersome and expensive. As the wearable inertial sensor has developed a lot, in this paper, we present a novel human action classification algorithm using in basketball, based on a single inertial sensor, which is a application of multi-label classification. We performed experiment on real world datasets. The AUPRC, AUROC and confusion matrix of our results demonstrated that our novel basketball motion recognizer have a great performance.

KW - Basketball motion

KW - Feature extraction

KW - Human action recognition

KW - Multi-label classification

KW - Single inertial sensor

KW - Support vector machine

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DO - 10.1007/978-981-10-7398-4_16

M3 - Conference contribution

AN - SCOPUS:85045974311

SN - 9789811073977

VL - 464

T3 - Lecture Notes in Electrical Engineering

SP - 152

EP - 161

BT - Frontier Computing - Theory, Technologies and Applications FC 2017

PB - Springer

Y2 - 12 July 2017 through 14 July 2017

ER -

Human action classification in basketball: A single inertial sensor based framework

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