Semi-automated development of a dataset for baseball pitch type recognition

Dylan Siegler; Reed Chen; Michael Fasko; Shunkun Yang; Xiong Luo; Wenbing Zhao

doi:10.1007/978-981-15-1925-3_25

Semi-automated development of a dataset for baseball pitch type recognition

Dylan Siegler
, Reed Chen
, Michael Fasko
, Shunkun Yang
, Xiong Luo
, Wenbing Zhao

Electrical and Computer Engineering

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

3 Scopus citations

Abstract

In this paper, we report our work on developing a new dataset for baseball pitch type recognition based on youtube videos of the US Major League Baseball games. The core innovation is a largely automated procedure to extract relevant clips from the full game, and automatically label the clips by aligning the infographic information included in the broadcast and the PitchF/X data. We adopted the Needleman-Wunsch algorithm to address the challenges imposed by the aligning the two streams of data based on pitch speed, i.e., minimize gaps and mismatches between the two streams. Manual inspection is used only to select games that include infographic information for clip extraction and to remove erroneous clips for improve the quality of the dataset.

Original language	English
Title of host publication	Communications in Computer and Information Science
Editors	Huansheng Ning
Place of Publication	che
Publisher	Springer
Pages	345-359
Number of pages	15
Volume	1138 CCIS
ISBN (Print)	9789811519246
DOIs	https://doi.org/10.1007/978-981-15-1925-3_25
State	Published - Jan 1 2019
Event	3rd International Conference on Cyberspace Data and Intelligence, Cyber DI 2019, and the International Conference on Cyber-Living, Cyber-Syndrome, and Cyber-Health, CyberLife 2019 - Beijing, China Duration: Dec 16 2019 → Dec 18 2019

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	1138 CCIS
ISSN (Print)	18650929
ISSN (Electronic)	18650937

Conference

Conference	3rd International Conference on Cyberspace Data and Intelligence, Cyber DI 2019, and the International Conference on Cyber-Living, Cyber-Syndrome, and Cyber-Health, CyberLife 2019
Country/Territory	China
City	Beijing
Period	12/16/19 → 12/18/19

Keywords

Dataset
Needleman-Wunsch algorithm
Pitch type
PitchF/X
Video-based human activity recognition

Access to Document

10.1007/978-981-15-1925-3_25

Cite this

Siegler, D., Chen, R., Fasko, M., Yang, S., Luo, X., & Zhao, W. (2019). Semi-automated development of a dataset for baseball pitch type recognition. In H. Ning (Ed.), Communications in Computer and Information Science (Vol. 1138 CCIS, pp. 345-359). (Communications in Computer and Information Science; Vol. 1138 CCIS). Springer. https://doi.org/10.1007/978-981-15-1925-3_25

@inproceedings{d191785f03304a5aa31cc764cc37e281,

title = "Semi-automated development of a dataset for baseball pitch type recognition",

abstract = "In this paper, we report our work on developing a new dataset for baseball pitch type recognition based on youtube videos of the US Major League Baseball games. The core innovation is a largely automated procedure to extract relevant clips from the full game, and automatically label the clips by aligning the infographic information included in the broadcast and the PitchF/X data. We adopted the Needleman-Wunsch algorithm to address the challenges imposed by the aligning the two streams of data based on pitch speed, i.e., minimize gaps and mismatches between the two streams. Manual inspection is used only to select games that include infographic information for clip extraction and to remove erroneous clips for improve the quality of the dataset.",

keywords = "Dataset, Needleman-Wunsch algorithm, Pitch type, PitchF/X, Video-based human activity recognition",

author = "Dylan Siegler and Reed Chen and Michael Fasko and Shunkun Yang and Xiong Luo and Wenbing Zhao",

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booktitle = "Communications in Computer and Information Science",

note = "3rd International Conference on Cyberspace Data and Intelligence, Cyber DI 2019, and the International Conference on Cyber-Living, Cyber-Syndrome, and Cyber-Health, CyberLife 2019 ; Conference date: 16-12-2019 Through 18-12-2019",

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Siegler, D, Chen, R, Fasko, M, Yang, S, Luo, X & Zhao, W 2019, Semi-automated development of a dataset for baseball pitch type recognition. in H Ning (ed.), Communications in Computer and Information Science. vol. 1138 CCIS, Communications in Computer and Information Science, vol. 1138 CCIS, Springer, che, pp. 345-359, 3rd International Conference on Cyberspace Data and Intelligence, Cyber DI 2019, and the International Conference on Cyber-Living, Cyber-Syndrome, and Cyber-Health, CyberLife 2019, Beijing, China, 12/16/19. https://doi.org/10.1007/978-981-15-1925-3_25

Semi-automated development of a dataset for baseball pitch type recognition. / Siegler, Dylan; Chen, Reed; Fasko, Michael et al.
Communications in Computer and Information Science. ed. / Huansheng Ning. Vol. 1138 CCIS che: Springer, 2019. p. 345-359 (Communications in Computer and Information Science; Vol. 1138 CCIS).

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

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Semi-automated development of a dataset for baseball pitch type recognition

Abstract

Publication series

Conference

Keywords

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