Capturing Captivating Moments: A Multi-Model Approach for Identifying Baseball Strikeout Highlights
學年 113
學期 1
出版（發表）日期 2025-01-23
作品名稱 Capturing Captivating Moments: A Multi-Model Approach for Identifying Baseball Strikeout Highlights
作品名稱（其他語言）
著者 Qiaoyun Zhang, Chih-Yung Chang, Cuijuan Shang ; Hsiang-Chuan Chang ; Diptendu Sinha Roy
單位
出版者
著錄名稱、卷期、頁數 Signal, Image and Video Processing 19(232)， p. 1-14
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.
關鍵字 Action recognition ;Object detection ;Heterogeneous features; Multi-model integration
語言 en
ISSN
期刊性質 國外
收錄於 SCI Scopus
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/126776 )

SDGS 尊嚴就業與經濟發展,產業創新與基礎設施