Detection of Important Scenes in Baseball Videos via Bidirectional Time Lag Aware Deep Multiset Canonical Correlation Analysis

Detection of Important Scenes in Baseball Videos via Bidirectional Time Lag Aware Deep Multiset Canonical Correlation Analysis

A novel method for detection of important scenes in baseball videos based on correlation maximization between heterogeneous modalities via bidirectional time lag aware deep multiset canonical correlation analysis (BiTl-dMCCA) is presented in this paper. The proposed method enables detection of impor...

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Bibliographic Details
Main Authors: Kaito Hirasawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Unsupervised important scene detection
time lag aware canonical correlation maximization
anomaly detection
generative adversarial network
Online Access:https://ieeexplore.ieee.org/document/9450798/

Internet

https://ieeexplore.ieee.org/document/9450798/

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