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Pedro Perona hat in einer viel beachteten Arbeit die Umsetzung einer VISIPEDIA als Fernziel für die Forschung im Bereich Computer Vision ausgemacht:
"The web is not perfect: while text is easily searched and organized, pictures (the vast majority |
Pattern Recognition techniques help make sense of data. Unsupervised methods can help explore vast data sets. Supervised methods use training data to infer rules that allow making valid predictions. Applications abound in fields ranging from astronomy to finance.
OpenGM is a C++ template library for discrete factor graph models and distributive operations on these models. It includes state-of-the-art optimization and inference algorithms beyond message passing. OpenGM handles large models efficiently, since (i) functions that occur repeatedly need to be stored only once and (ii) when functions require different parametric or non-parametric encodings, multiple encodings can be used alongside each other, in the same model, using included and custom C++ code. No restrictions are imposed on the factor graph or the operations of the model. OpenGM is modular and extendible. Elementary data types can be chosen to maximize efficiency. The graphical model data structure, inference algorithms and different encodings of functions inter-operate through well-defined interfaces. The binary OpenGM file format is based on the HDF5 standard and incorporates user extensions automatically.
