OBJ CUT
OBJ CUT is an efficient method that automatically segments an object. The OBJ CUT method is a generic method, and therefore it is applicable to any object category model. Given an image D containing an instance of a known object category, e.g. cows, the OBJ CUT algorithm computes a segmentation of the object, that is, it infers a set of labels m.
Let m be a set of binary labels, and let be a shape parameter( is a shape prior on the labels from a layered pictorial structure (LPS) model). An energy function is defined as follows.
- (1)
The term is called a unary term, and the term is called a pairwise term. A unary term consists of the likelihood based on color, and the unary potential based on the distance from . A pairwise term consists of a prior and a contrast term .
The best labeling minimizes, where is the weight of the parameter .
- (2)
Read more about this topic: Segmentation-based Object Categorization
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“The whole cut impressed me as if it were a cave with its stalactites laid open to the light.”
—Henry David Thoreau (1817–1862)