Egocentric videos can bring a lot of information about how humans perceive the world and interact with the environment, which can be beneficial for the analysis of human behaviour. The research in egocentric video analysis is developing rapidly thanks to the increasing availability of wearable devices and the opportunities offered by new large-scale egocentric datasets. As computer vision techniques continue to develop at an increasing pace, the tasks related to the prediction of future are starting to evolve from the need of understanding the present. Predicting future human activities, trajectories and interactions with objects is crucial in applications such as human-robot interaction, assistive wearable technologies for both industrial and daily living scenarios, entertainment and virtual or augmented reality. This survey summarises the evolution of studies in the context of future prediction from egocentric vision making an overview of applications, devices, existing problems, commonly used datasets, models and input modalities. Our analysis highlights that methods for future prediction from egocentric vision can have a significant impact in a range of applications and that further research efforts should be devoted to the standardisation of tasks and the proposal of datasets considering real-world scenarios such as the ones with an industrial vocation.

翻译：以地球为中心的视频可以带来大量关于人类如何看待世界和如何与环境互动的信息,这有利于分析人类行为。自我中心视频分析的研究正在迅速发展,因为越来越多的可磨损设备和新的大型以自我为中心的数据集所提供的机会越来越多。随着计算机视觉技术继续以越来越快的速度发展,与预测未来有关的任务开始从了解当前需要开始。预测未来人类活动、轨迹和与物体的相互作用对于应用人类机器人互动、工业和日常生活情景、娱乐和虚拟或扩大现实的辅助性可磨损技术至关重要。这一调查总结了未来预测背景下研究的演变,从以自我中心视角概述各种应用、装置、现有问题、常用数据集、模型和输入模式。我们的分析强调,从以自我中心视角预测未来的方法可在一系列应用中产生重大影响,进一步的研究努力应致力于任务的标准化和考虑到现实世界情景的建议,例如工业目标。