| Abstrakt: |
Affordance refers to a series of interaction possibilities provided by objects in the environment, and describes the connection process between environmental attributes and individuals. Among them, visual affordance research is to use visual data such as images and videos to explore the possibility of visual subjects interacting with the environment or objects, involving scene recognition, action recognition, object detection, and other related fields. Visual affordance can be widely used in robotics, scene understanding, and other fields. Based on a large number of literature reviews, the visual affordance is classified and expounded according to three aspects: functional affordance, behavioral affordance, and social affordance. And for each type of affordability detection method, it is discussed in detail according to traditional machine learning methods and deep learning methods. At the same time, the current typical visual affordance datasets are summarized and analyzed, the application direction of visual affordance and possible future research directions are discussed. [ABSTRACT FROM AUTHOR] |
