Section: New Results

Inference of Procedural Grammars from Images

Paticipants: Nikos Paragios

Grammar-like representations are powerful modeling and inference tools in computational vision. In  [39] a novel approach towards automatic inference of typology specific building grammars has been introduced. The central idea was to consider that such grammars could be derived through a bottom up approach of common sub-tree reasoning of derivation trees determined through parsing using elementary shape (binary split) grammars. Such an approach performs common subtree reduction within the entire training set and identifies meta-rules (corresponding to the same subtrees) which are then clustered together towards producing a compact, typology specific grammar. Promising results both in terms of grammar compactness as well as in terms of inference demonstrated the potentials of the method that could be used beyond the considered scoped.