Random Polyhedral Scenes: An Image Generator for Active Vision System Experiments

TL;DR

This paper introduces a polyhedral scene generator that creates randomized scenes with annotations, supporting active perception research by providing diverse, verifiable datasets from multiple viewpoints without needing a live environment.

Contribution

The system enables generation of complex, annotated polyhedral scenes from various viewpoints, facilitating active perception research without real-time 3D environments.

Findings

Supports research in active perception with verifiable scene datasets

Generates scenes with known complexity and feature distribution

Publicly available for community use

Abstract

We present a Polyhedral Scene Generator system which creates a random scene based on a few user parameters, renders the scene from random view points and creates a dataset containing the renderings and corresponding annotation files. We hope that this generator will enable research on how a program could parse a scene if it had multiple viewpoints to consider. For ambiguous scenes, typically people move their head or change their position to see the scene from different angles as well as seeing how it changes while they move; this research field is called active perception. The random scene generator presented is designed to support research in this field by generating images of scenes with known complexity characteristics and with verifiable properties with respect to the distribution of features across a population. Thus, it is well-suited for research in active perception without the requirement of a live 3D environment and mobile sensing agent, including comparative performance evaluations. The system is publicly available at https://polyhedral.eecs.yorku.ca.