The visual perception of object affordances has emerged as a useful ingredient for building powerful computer vision and robotic applications. In this project we introduce a novel approach to reason about liquid containability – the affordance of containing liquid. Our approach analyzes container objects based on two simple physical processes: the Fill and Transfer of liquid. First, it reasons about whether a given 3D object is a liquid container and its best filling direction. Second, it proposes directions to transfer its contained liquid to the outside while avoiding spillage. We compare our simplified model with a common fluid dynamics simulation and demonstrate that our algorithm makes human-like choices about the best directions to fill containers and transfer liquid from them. We apply our approach to reason about the containability of several real-world objects acquired using a consumer-grade depth camera.

This project is one example of functional analysis of a 3D shape. It is related to thrust 1.2.2 Computational Design – Multi-functional analysis. By analyzing the containability, we can design and manufacture novel container without affecting its core function – containing liquid. This project is related to another project – Zoomorphic Design. Preliminary results of this project are published in the prestigious computer vision conference – IEEE International Conference on Computer Vision (ICCV) 2015.