constrained-sdd 0.1.0

A Python package for working with constrained Stanford Drone Dataset.

Constrained-SDD

This repository contains an annotated version of the Stanford Drone Dataset[1]. We segmented the first 50 images from SDD and drew polygons for buildings, obstacles and offroad. Our trajectories only follow the roads/walking paths.

Citation

Leander Kurscheidt, Paolo Morettin, Roberto Sebastiani, Andrea Passerini, Antonio Vergari, A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction, (to appear)

Examples

An overview over all the images can be seen in analysis/viz_data.ipynb.

Further Details

We annotate the first 50 pictures (scenes in the original dataset) with trajectories of the Stanford Drone Dataset[1], as extracted by P2T[2]. We select all trajectories following the road and delete obvious errors, like projecting a trajectory that slightly touches a building outwards and deleting trajectories that suddenly jump around. We annotate using three classes: Building, Obstacle and Offroad, which forms our constraint-set. Additionally, we have annotated the entrance of a building to differentiate trajectories that enter a building from those who not, but this is unused. All trajectories in our dataset are constraint-abiding.

[1] A. Robicquet, A. Sadeghian, A. Alahi, S. Savarese, Learning Social Etiquette: Human Trajectory Prediction In Crowded Scenes in European Conference on Computer Vision (ECCV), 2016. [2] Nachiket Deo, Mohan M. Trivedi, Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans, 2021