DeepAI AI Chat
Log In Sign Up

Learning a Pedestrian Social Behavior Dictionary

by   Faith Johnson, et al.
Rutgers University

Understanding pedestrian behavior patterns is a key component to building autonomous agents that can navigate among humans. We seek a learned dictionary of pedestrian behavior to obtain a semantic description of pedestrian trajectories. Supervised methods for dictionary learning are impractical since pedestrian behaviors may be unknown a priori and the process of manually generating behavior labels is prohibitively time consuming. We instead utilize a novel, unsupervised framework to create a taxonomy of pedestrian behavior observed in a specific space. First, we learn a trajectory latent space that enables unsupervised clustering to create an interpretable pedestrian behavior dictionary. We show the utility of this dictionary for building pedestrian behavior maps to visualize space usage patterns and for computing the distributions of behaviors. We demonstrate a simple but effective trajectory prediction by conditioning on these behavior labels. While many trajectory analysis methods rely on RNNs or transformers, we develop a lightweight, low-parameter approach and show results comparable to SOTA on the ETH and UCY datasets.


page 1

page 3

page 4

page 5

page 6

page 7


Semantic segmentation of trajectories with improved agent models for pedestrian behavior analysis

In this paper, we propose a method for semantic segmentation of pedestri...

STGlow: A Flow-based Generative Framework with Dual Graphormer for Pedestrian Trajectory Prediction

Pedestrian trajectory prediction task is an essential component of intel...

Towards Rich, Portable, and Large-Scale Pedestrian Data Collection

Recently, pedestrian behavior research has shifted towards machine learn...

An End-to-End Learning Approach for Trajectory Prediction in Pedestrian Zones

This paper aims to explore the problem of trajectory prediction in heter...

PSI: A Pedestrian Behavior Dataset for Socially Intelligent Autonomous Car

Prediction of pedestrian behavior is critical for fully autonomous vehic...

Pedestrian Detection by Exemplar-Guided Contrastive Learning

Typical methods for pedestrian detection focus on either tackling mutual...

A Transferable Pedestrian Motion Prediction Model for Intersections with Different Geometries

This paper presents a novel framework for accurate pedestrian intent pre...