Bismarck and the Creation of the Second Reich

Chancellor Otto Bismarck's "greatness" lay in what he created, the German Reich of 1871. This Reich was the product of his genius, and in it his genius took complete shape. In less than a decade German chaos was brought to an end and in its place a homogeneous state began to arise. The structure of this state left no room for opposing political forces, but rather made ready a roof under which these forces might rally, support each other, and gain strength. Bismarck and the Creation of the Second Reich begins as a biography but continues as a description of his political life and the ideas that led to the birth of an authoritarian political culture.The community from which Bismarck formed his conception of the state was first the family and clan, then the landlord caste, and finally the people. These communities found their unifying force in the Kaiser, who as their patriarchal head enjoyed divine honors as ruler by the grace of God. The existence of the state was justified as the framework within which these communities existed, and it had thus a biological as well as a religious content. This idea of the state as the supreme moral command of religion was too powerful a driving force to be dropped in favor of the rational view of the state as a potential war machine. Bismarck reconciled the two concepts by use of the concept of a "people in arms," an idea which had originated in German history as a means of defense, but which was changed into one of aggression. In order to become a means of aggression it was changed into a moral precept commanded by religion, and indeed into the supreme precept.Through the unfolding of the political life of Bismarck, we find the roots of the Nazi Third Reich--the inability of the people to educate themselves about politics enough to effect any change or satisfy their own political needs. In this loss of control, the authoritarian regime grew stronger. Though Bismarck's work led to the creation and implementation of the Second Reich, "it is in the Third Reich that we find the devilish distortion that was its fruit." This volume is an essential tool for understanding twentieth-century German history.

Friedrich Darmstaedter was former lecturer in philosophy of law and state, Heidelberg and Rome. He is also the author of Political Tendencies from Frederick the Great to Hitler. Eda Sagarra is professor of Germanic Studies at Trinity College, University of Dublin. She is the author of A Social History of Germany 1648-1914 (available from Transaction).

Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables systematic development of optimal vision algorithms when used with optimization principles. This detailed and thoroughly enhanced third edition presents a comprehensive study / reference to theories, methodologies and recent developments in solving computer vision problems based on MRFs, statistics and optimization. It treats various problems in low- and high-level computational vision in a systematic and unified way within the MAP-MRF framework. Among the main issues covered are: how to use MRFs to encode contextual constraints that are indispensable to image understanding; how to derive the objective function for the optimal solution to a problem; and how to design computational algorithms for finding an optimal solution. Easy-to-follow and coherent, the revised edition is accessible, includes the most recent advances, and has new and expanded sections on such topics as:Conditional Random Fields; Discriminative Random Fields;Total Variation (TV) Models;Spatio-temporal Models;MRF and Bayesian Network (Graphical Models); Belief Propagation; Graph Cuts;and Face Detection and Recognition. Features: Focuses on applying Markov random fields to computer vision problems, such as image restoration and edge detection in the low-level domain, and object matching and recognition in the high-level domain Introduces readers to the basic concepts, important models and various special classes of MRFs on the regular image lattice, and MRFs on relational graphs derived from images Presents various vision models in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation Uses a variety of examples to illustrate how to convert a specific vision problem involving uncertainties and constraints into essentially an optimization problem under the MRF setting Studies discontinuities, an important issue in the application of MRFs to image analysis Examines the problems of model parameter estimation and function optimization in the context of texture analysis and object recognition * Includes an extensive list of references This broad-ranging and comprehensive volume is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses relating to these areas.

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