Titlebook: Data Fusion for Sensory Information Processing Systems; James J. Clark,Alan L. Yuille Book 1990 Springer-Verlag US 1990 Frames.Stereo.algo

大雨

ENNUI

Data Fusion Applied to Feature Based Stereo Algorithms,esian approach to vision outlined in chapters 2 and 3, in particular in terms of coupled Markov Random Fields. We show that this formalism is rich enough to contain most of the elements used in standard stereo theories.

interference

攝取

idiopathic

Indolent

Indicative

Fusing Binocular and Monocular Depth Cues, different features that described in the previous chapter can be naturally extended to incorporate these additional cues. Again methods from statistical mechanics, or statistics, can be applied to impose the matching constraints in a “strong” manner.

起來了

祖先

Nuclear Transitions and Radioactive Decayhave looked towards these studies in search of clues as to how machines can be made to gather and process information. In this book we focus on an important aspect of sensory information processing, that of fusing separate sources of sensory information.

云狀

Jos Dobber,José Harmsen,Margriet van Ierselect shape from shading information. The first example is of an algebraic approach, while the second involves an energy function or Bayesian approach. We follow this description of the weakly coupled methods with an illustration of how we can convert the weakly coupled fusion algorithms into a strongly coupled fusion algorithm.