Rodríguez-Moreno Itsaso, Martínez-Otzeta José María, Sierra Basilio, Rodriguez Igor, Jauregi Ekaitz
Department of Computer Science and Artificial Intelligence, University of the Basque Country, Manuel Lardizabal 1, 20018 Donostia-San Sebastián, Spain.
Department of Computer Languages and Systems, University of the Basque Country, Manuel Lardizabal 1, 20018 Donostia-San Sebastián, Spain.
Sensors (Basel). 2019 Jul 18;19(14):3160. doi: 10.3390/s19143160.
Video activity recognition, although being an emerging task, has been the subject of important research efforts due to the importance of its everyday applications. Surveillance by video cameras could benefit greatly by advances in this field. In the area of robotics, the tasks of autonomous navigation or social interaction could also take advantage of the knowledge extracted from live video recording. The aim of this paper is to survey the state-of-the-art techniques for video activity recognition while at the same time mentioning other techniques used for the same task that the research community has known for several years. For each of the analyzed methods, its contribution over previous works and the proposed approach performance are discussed.
视频活动识别虽然是一个新兴任务，但由于其在日常应用中的重要性，已成为重要的研究课题。摄像机监控可从该领域的进展中大大受益。在机器人技术领域，自主导航或社交互动任务也可利用从实时视频记录中提取的知识。本文的目的是调查视频活动识别的最新技术，同时提及研究界多年来已知的用于同一任务的其他技术。对于每种分析方法，都讨论了其相对于先前工作的贡献以及所提出方法的性能。
