Object Detection using HoG Features for Visual Situation Recognition

This project investigates a novel approach to building computer systems that can recognize visual situations. While much effort in computer vision has focused on identifying isolated objects in images, what people actually do is recognize coherent situations — collections of objects and their interrelations that, taken together, correspond to a known concept, such as "dog-walking", or "a fight breaking out", or "a blind person crossing the street". Situation recognition by humans may appear on the surface to be effortless, but it relies on a complex dynamic interplay among human abilities to perceive objects, systems of relationships among objects, and analogies with stored knowledge and memories. Enabling computers to flexibly recognize visual situations would create a flood of important applications in fields as diverse as autonomous vehicles, medical diagnosis, interpretation of scientific imagery, enhanced humancomputer interaction, and personal information organization.