By Song-Chun Zhu, David Mumford
A Stochastic Grammar of pictures is the 1st booklet to supply a foundational overview and viewpoint of grammatical ways to computing device imaginative and prescient. In its quest for a stochastic and context delicate grammar of pictures, it really is meant to function a unified frame-work of illustration, studying, and popularity for a lot of item different types. It begins out by means of addressing the historical tendencies within the sector and overviewing the most ideas: equivalent to the and-or graph, the parse graph, the dictionary and is going directly to studying matters, semantic gaps among symbols and pixels, dataset for studying and algorithms. The concept grammar provided integrates 3 favorite representations within the literature: stochastic grammars for composition, Markov (or graphical) versions for contexts, and sparse coding with primitives (wavelets). It additionally combines the structure-based and visual appeal dependent equipment within the imaginative and prescient literature. on the finish of the assessment, 3 case experiences are provided to demonstrate the proposed grammar. A Stochastic Grammar of pictures is a vital contribution to the literature on established statistical versions in machine imaginative and prescient.
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Extra resources for A Stochastic Grammar of Images
A) An input image I. (b) The sketch graph – conﬁguration computed from the image I. (c) The pixels in the sketchable part Λsk . (d) The remaining non-sketchable portion are textures, which are segmented into a small number of homogeneous regions in (e). (f) The ﬁnal synthesized image integrating seamlessly the structures and textures. From . 46 Visual Vocabulary The remaining pixels are ﬂat or stochastic texture areas, called nonsketchable, and are clustered into a few homogeneous texture areas nnsk Λnsk = Λ\Λsk = Λnsk,j .
The grammar rules represent both structural regularity and ﬂexibility. The structural regularity is enforced by the template which decomposes an entity A, such as object into certain elements in β. The structural ﬂexibility is reﬂected by the fact that each structure A has many alternative decompositions. In this paper, we will ﬁnd it convenient to describe the entire grammar by one universal And–Or tree, which contains all parsings as subtrees. In this tree, the Or-nodes are labeled by VN ∪ VT and the And-nodes are labeled by production rules R.
7(b). One “solution” to this issue is to choose, once and for all, one of these as the preferred parse for a square. In analyzing the image, both parses may occur but, in order to give the whole the “square” label, one parse is chosen and the other parts representing partial structures are rejected. “Joints” will be studied below: often two parts of the image are combined in characteristic geometric ways. For example, two thin rectangles may butt against each other and then form a compound part.