arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2003.09970cs.CV

The Instantaneous Accuracy: a Novel Metric for the Problem of Online Human Behaviour Recognition in Untrimmed Videos

University of Alcalá(阿尔卡拉大学);Adobe Research(Adobe研究院);Delft University of Technology(代尔夫特理工大学)

Marcos Baptista Rios, Roberto J. López-Sastre, Fabian Caba Heilbron, Jan van Gemert, Francisco Javier Acevedo-Rodríguez, Saturnino Maldonado-Bascón

英文摘要:

The problem of Online Human Behaviour Recognition in untrimmed videos, aka Online Action Detection (OAD), needs to be revisited. Unlike traditional offline action detection approaches, where the evaluation metrics are clear and well established, in the OAD setting we find few works and no consensus on the evaluation protocols to be used. In this paper we introduce a novel online metric, the Instantaneous Accuracy ($IA$), that exhibits an \emph{online} nature, solving most of the limitations of the previous (offline) metrics. We conduct a thorough experimental evaluation on TVSeries dataset, comparing the performance of various baseline methods to the state of the art. Our results confirm the problems of previous evaluation protocols, and suggest that an IA-based protocol is more adequate to the online scenario for human behaviour understanding. Code of the metric available https://github.com/gramuah/ia

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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