Fill and Transfer: A Simple Physics-Based Approach for Containability Reasoning

Lap-Fai Yu, Noah Duncan, Sai-Kit Yeung; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2015, pp. 711-719

The visual perception of object affordances has emerged as a useful ingredient for building powerful computer vision and robotic applications. In this paper 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.