Capturing Captivating Moments: A Multi-Model Approach for Identifying Baseball Strikeout Highlights

doi:10.1007/s11760-024-03805-x

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 期刊論文 > Item 987654321/126776

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/126776

题名:	Capturing Captivating Moments: A Multi-Model Approach for Identifying Baseball Strikeout Highlights
作者:	Qiaoyun Zhang, Chih-Yung Chang, Cuijuan Shang;Chang, Hsiang-Chuan;Roy, Diptendu Sinha
关键词:	Action recognition;Object detection;Heterogeneous features;Multi-model integration
日期:	2025-01-23
上传时间:	2025-03-20 09:24:21 (UTC+8)
摘要:	With the extensive popularity of baseball, fans are eager to relive exciting moments such as strikeouts, catching, and home runs. However, manually extracting these highlights from long videos is time-consuming and labor-intensive. To address this, this paper introduces a mechanism called CCM (capturing captivating moments), which aims to effectively identify baseball strikeout highlights. Initially, the proposed CCM employs a coarse-grain policy that involves two key components. Firstly, it utilizes You Only Look Once (YOLO) to detect the change of out-indicator in video frames. Secondly, it employs long short-term memory to analyze the skeleton features of athletes, aiming to extract the draft segments as the candidates that contain the strikeout. Then a fine-grain policy integrates YOLOv5, bidirectional encoder representations from transformers, and 3D convolutional neural networks to accurately identify the strikeout highlights. By combining heterogeneous features and multi-model integration, the proposed CCM ensures robust and precise identification of captivating strikeout moments in baseball videos. The simulation results demonstrate that the proposed CCM outperforms the existing mechanisms in terms of accuracy, recall, precision, and F1-score.
關聯:	Signal, Image and Video Processing 19(232)， p. 1-14
DOI:	10.1007/s11760-024-03805-x
显示于类别:	[資訊工程學系暨研究所] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
index.html		0Kb	HTML	17	检视/开启

在機構典藏中所有的数据项都受到原著作权保护.

TAIR相关文章

数据加载中.....