Automatic discovery of groups of objects for scene understanding

Objects in scenes interact with each other in complex ways. A key observation is that these interactions manifest themselves as predictable visual patterns in the image. Discovering and detecting these structured patterns is an important step towards deeper scene understanding. It goes beyond using either individual objects or the scene as a whole as the semantic unit. In this work, we promote “groups of objects”. They are high-order composites of objects that demonstrate consistent spatial, scale, and viewpoint interactions with each other. These groups of objects are likely to correspond to a specific layout of the scene. They can thus provide cues for the scene category and can also prime the likely locations of other objects in the scene. It is not feasible to manually generate a list of all possible groupings of objects we find in our visual world. Hence, we propose an algorithm that automatically discovers groups of arbitrary numbers of participating objects from a collect...

• Type: Journal
• Year: 2012
• Where: CVPR
• Authors: Congcong Li, Devi Parikh, Tsuhan Chen
• Keywords: Arbitrary Numbers, Computer Vision, Cvpr 2012, Groupings Of Objects, Object Categories