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STOCHASTIC TRAJECTORY PREDICTION USING SOCIAL GRAPH NETWORKS

机译:使用社会图网络的随机轨迹预测

摘要

Systems, methods, apparatuses, and computer program products to provide stochastic trajectory prediction using social graph networks. An operation may comprise determining a first feature vector describing destination features of a first person depicted in an image, generating a directed graph for the image based on all people depicted in the image, determining, for the first person, a second feature vector based on the directed graph and the destination features, sampling a value of a latent variable from a learned prior distribution, the latent variable to correspond to a first time interval, and generating, based on the sampled value and the feature vectors by a hierarchical long short-term memory (LSTM) executing on a processor, an output vector comprising a direction of movement and a speed of the direction of movement of the first person at a second time interval, subsequent to the first time interval.
机译:系统,方法,装置和计算机程序产品使用社交图网络提供随机轨迹预测。操作可以包括确定描述在图像中描绘的第一人称的目的地特征的第一特征向量,基于图像中描绘的所有人,为第一人称,基于的所有人来生成用于图像的定向图。定向图和目的地特征,从学习的先前分发采样潜​​在变量的值,潜在的变量对应于第一时间间隔,并根据采样值和特征向量通过分层长短短路生成在处理器上执行术语存储器(LSTM),输出向量包括移动方向和第一人在第一次间隔之后的第二时间间隔的移动方向的速度。

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