行動認識arXiv:1905.05420
実環境向け骨格ベース行動認識フレームワーク
Towards a Skeleton-Based Action Recognition For Realistic Scenarios
骨格情報を用いた行動認識を実用的なシナリオで使えるよう検討し、データ拡張や正規化なしでは別データセットで性能が大きく低下することを示した。
著者: Cagatay Odabasi, Jewel Jose
分類: cs.RO, cs.CV
原文アブストラクト
Understanding human actions is a crucial problem for service robots. However, the general trend in Action Recognition is developing and testing these systems on structured datasets. That's why this work presents a practical Skeleton-based Action Recognition framework which can be used in realistic scenarios. Our results show that although non-augmented and non-normalized data may yield comparable results on the test split of the dataset, it is far from being useful on another dataset which is a manually collected data.