德国博世公司研究所在2019年12月17日arXiv上传综述论文“Human Motion Trajectory Prediction: A Survey“。 摘要:人类环境中出现越来越多的智能自主系统,其系统感知、理解和预期人类行为的能力变得越来越重要。 具体而言,预测动态代理的未来位置并以此预测进行规划是自动驾驶车辆、服务机器人和高级监控系统(包括智能交通或...
Human trajectory prediction is an important topic in several application domains, ranging from self-driving cars to environment design and planning, from socially-aware robots to intelligent tracking systems. This complex subject comes with different challenges, such as human-space interaction, human-...
deep-learningautonomous-vehicleshuman-robot-interactionspatio-temporal-predictionhuman-trajectory-predictionnuscenes UpdatedAug 17, 2023 Jupyter Notebook abduallahmohamed/Social-STGCNN Star495 Code Issues Pull requests Code for "Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Huma...
文章通过一种新的池化策略连接相邻的LSTM来解决这一问题。 将邻居的隐藏状态(以黄色、蓝色和橙色显示)集中在一定的空间距离内。池化部分保留了邻域的空间信息 文章中对场景中的每个轨迹使用单独的LSTM网络,LSTM通过社交池化(S-Pooling)层彼此连接。与传统的LSTM不同,这种池化层允许空间上邻近的LSTM彼此共享信息。在特定...
Introvert: Human Trajectory Prediction via Conditional 3D Attention Nasim Shafiee Northeastern University shafiee.n@northeastern.edu Taskin Padir Northeastern University t.padir@northeastern.edu Ehsan Elhamifar Northeastern University e.elhamifar@northeastern.edu Abstract Predicting ...
Human Trajectory Prediction Benchmarks Toolkit To download the toolkit, separately in a zip file click:here Using python files inbenchmarking/indicatorsdir, you can generate the results of each of the indicators presented in the article. For more information about each of the scripts check the in...
This problem of trajectory prediction can be viewed as a sequence generation task, where we are interested in predicting the future trajectory of people based on their past positions. Following the recent success of Recurrent Neural Network (RNN) models for sequence prediction tasks, we propose an...
Human Intention Understanding and Trajectory Planning Based on Multi-modal Data This paper presents a framework of human intention reasoning and trajectory prediction based on multi-modal information. It mainly consists of two parts: ... C Liu,X Cao,X Li - International Conference on Cognitive Syst...
概览 简述 文献所提出的模型旨在解决交通中行人的轨迹预测(pedestrian trajectory prediction)问题,特别是在拥挤环境中——人与人交互(interaction)行为常有发生的地方。 文献构建的数据驱动模型,利用在序列预测上表现突出的 LSTM模型 以行人为单位进行轨迹预测
论文阅读:Social LSTM: Human Trajectory Prediction in Crowded Spaces,程序员大本营,技术文章内容聚合第一站。