Dynami Positional Trees for Stru tural Image Analysis
We onsider the problem of stru tural image analysis and in parti ular the inferen e of s ene properties from image data. We are espe ially on erned with image de omposition, that is obtaining the hara teristi parts of an image and the relationships between them. The omponents of an image are not independent of ea h other; ertain obje ts are expe ted to o ur together, and obje ts are made up of di erent sub omponents. One way of thinking of this problem is by analogy with parsing a language; we are interested in parsing images. However, the important hara teristi s and stru ture in an image is signi antly di erent from linguisti data.