Modeling the dynamics of people walking is a problem of long-standing interest in computer vision. Many previous works involving pedestrian trajectory prediction define a particular set of individual actions to implicitly model group actions. In this paper, we present a novel architecture named GP-Graph which has collective group representations for effective pedestrian trajectory prediction in crowded environments, and is compatible with all types of existing approaches. A key idea of GP-Graph is to model both individual-wise and group-wise relations as graph representations. To do this, GP-Graph first learns to assign each pedestrian into the most likely behavior group. Using this assignment information, GP-Graph then forms both intra- and inter-group interactions as graphs, accounting for human-human relations within a group and group-group relations, respectively. To be specific, for the intra-group interaction, we mask pedestrian graph edges out of an associated group. We also propose group pooling&unpooling operations to represent a group with multiple pedestrians as one graph node. Lastly, GP-Graph infers a probability map for socially-acceptable future trajectories from the integrated features of both group interactions. Moreover, we introduce a group-level latent vector sampling to ensure collective inferences over a set of possible future trajectories. Extensive experiments are conducted to validate the effectiveness of our architecture, which demonstrates consistent performance improvements with publicly available benchmarks. Code is publicly available at https://github.com/inhwanbae/GPGraph.
翻译:模拟行人行走的动态是一个长期对计算机视觉感兴趣的问题。 许多以前涉及行人轨迹预测的工程都界定了一组特定的个人行动,以隐含式群落行动。 在本文中,我们展示了一个名为GP-Graph的新颖结构,该结构集体代表了在拥挤环境中有效行人轨预测,并与所有类型的现有方法相兼容。 GP-Graph 的关键理念是将个人与群体之间的关系建模成图示式。为此,GP-Graph首先学会将每个行人指派到最有可能的行为组中。使用这一任务信息,GP-Graph 然后将群体内部和群体间的互动制成图表,在组内和群体群体间的关系中分别核算人与人之间的关系。具体地说,我们将行人图边缘遮盖起来,作为图示示式表示。为了代表一个多行人群体,GP-GP-Graph首先学习将每个行人指派到最有可能的行为组。 GGP-Graph推出一个可供社会接受的未来轨迹的概率图图图图,从一个综合的群组和群体-人类人际群间关系中,从一个可公开的模型到一个可公开的模级级级级级级级的模拟的校标,将一个可操作的校内,将一个可操作的校正标化到一个可操作。