典型文献
Trajectory distributions:A new description of movement for trajectory prediction
文献摘要：
Trajectory prediction is a fundamental and challenging task for numerous applications,such as autonomous driving and intelligent robots.Current works typically treat pedestrian trajectories as a series of 2D point coordinates.However,in real scenarios,the trajectory often exhibits randomness,and has its own probability distribution.Inspired by this observation and other movement characteristics of pedestrians,we propose a simple and intuitive movement description called a trajectory distribution,which maps the coordinates of the pedestrian trajectory to a 2D Gaussian distribution in space.Based on this novel description,we develop a new trajectory prediction method,which we call the social probability method.The method combines trajectory distributions and powerful convolutional recurrent neural networks.Both the input and output of our method are trajectory distributions,which provide the recurrent neural network with sufficient spatial and random information about moving pedestrians.Furthermore,the social probability method extracts spatio-temporal features directly from the new movement description to generate robust and accurate predictions.Experiments on public benchmark datasets show the effectiveness of the proposed method.
文献关键词：
中图分类号：
作者姓名：
Pei Lv;Hui Wei;Tianxin Gu;Yuzhen Zhang;Xiaoheng Jiang;Bing Zhou;Mingliang Xu
作者机构：
School of Information Engineering,Zhengzhou University,Zhengzhou 450001,China
文献出处：
引用格式：
[1]Pei Lv;Hui Wei;Tianxin Gu;Yuzhen Zhang;Xiaoheng Jiang;Bing Zhou;Mingliang Xu-.Trajectory distributions:A new description of movement for trajectory prediction)[J].计算可视媒体（英文）,2022(02):213-224
A类：
B类：
Trajectory,distributions,new,description,movement,trajectory,fundamental,challenging,task,numerous,applications,such,autonomous,driving,intelligent,robots,Current,typically,treat,trajectories,series,2D,point,coordinates,However,real,scenarios,often,exhibits,randomness,has,own,probability,Inspired,by,this,observation,other,characteristics,pedestrians,simple,intuitive,called,which,maps,Gaussian,space,Based,novel,develop,method,social,combines,powerful,convolutional,recurrent,neural,networks,Both,input,output,our,are,provide,sufficient,spatial,information,about,moving,Furthermore,extracts,spatio,temporal,features,directly,from,generate,robust,accurate,predictions,Experiments,public,benchmark,datasets,show,effectiveness,proposed
AB值：
0.563708
相似文献
机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
