Detection of unusual trajectories of moving objects (e.g., people, automobiles, etc.) is an important problem in many civilian and military surveillance applications. In this work, we propose a multi-objective evolutionary algorithms and rough sets-based approach that breaks down 2-dimensional trajectories into a set of additive components, which then can be used to build a classifier capable of recognizing typical, but yet unseen trajectories, and identifying those that seem suspicious.

Choreografish is a virtual reality, therapeutic arts engagement leveraging participatory research and design to collaborate with young adults with autism spectrum disorder (ASD). The research team was motivated by the social anxiety some with ASD have, and the attendant difficulties accessing art forms that may actually play well to Autism Spectrum Advantages (ASA). This project was co-designed with youth with ASA to explore the use of VR and choreographic thinking to empower users and designers to engage with the arts and self-manage anxiety. This paper describes the project, and gives a brief design history of Choreografish.