论文标题
没有看到即将到来：一项关于非语言社会人类行为预测的调查
Didn't see that coming: a survey on non-verbal social human behavior forecasting
论文作者
论文摘要
近年来，非语言社会人类行为预测越来越吸引研究界的兴趣。它直接应用于人类机器人的互动和具有社会意识的人类运动产生，使其成为一个非常有吸引力的领域。在这项调查中，我们以通用方式定义了多种互动代理的行为预测问题，旨在统一社会信号预测和人类运动预测的领域，传统上是分开的。我们认为，这两种问题的表述都涉及相同的概念问题，并确定许多共同的基本挑战：未来的随机性，上下文意识，历史剥削等。我们还提出了一种分类法，该分类法包括过去5年中非常有用的方式发表的方法，并描述了社区当前有关此问题的主要关注点。为了促进有关该领域的进一步研究，我们还提供了一个概述且友好的概述，概述了具有非作用社交互动的视听数据集。最后，我们描述了该任务中使用的最常见的指标及其特定问题。
Non-verbal social human behavior forecasting has increasingly attracted the interest of the research community in recent years. Its direct applications to human-robot interaction and socially-aware human motion generation make it a very attractive field. In this survey, we define the behavior forecasting problem for multiple interactive agents in a generic way that aims at unifying the fields of social signals prediction and human motion forecasting, traditionally separated. We hold that both problem formulations refer to the same conceptual problem, and identify many shared fundamental challenges: future stochasticity, context awareness, history exploitation, etc. We also propose a taxonomy that comprises methods published in the last 5 years in a very informative way and describes the current main concerns of the community with regard to this problem. In order to promote further research on this field, we also provide a summarised and friendly overview of audiovisual datasets featuring non-acted social interactions. Finally, we describe the most common metrics used in this task and their particular issues.
