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

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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