  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.
