Name
Abstract | ||
|---|---|---|
The visual perception of object affordances has emerged as a useful ingredient for building powerful computer vision and robotic applications [31]. 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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICCV.2015.88 | ICCV '15 Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV) |
Keywords | Field | DocType |
fill and transfer,physics-based approach,containability reasoning,visual perception,object affordance,computer vision,liquid container,filling direction,fluid dynamics simulation,depth camera | Computer vision,Computer science,Fluid dynamics,Spillage,Artificial intelligence,Affordance,Visual perception | Conference |
Volume | Issue | ISSN |
2015 | 1 | 1550-5499 |
Citations | PageRank | References |
6 | 0.40 | 29 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lap-Fai Yu | 1 | 316 | 24.87 |
| noah duncan | 2 | 13 | 1.15 |
| Sai Kit Yeung | 3 | 60 | 4.97 |