ions for Shape Analysis Predicate abstraction is a method for constrained-based abstraction that has been successfully applied in many domains. Unfortunately, in the context of shape analysis it is in general not efficient enough. In [5], we describe a new approach to shape analysis based on predicate abstraction. We propose a class of state predicates that exploits existent abstractions for sh...

sensor independent features. Different physical quantities can provide the same abstract information about an activity. Thus, for example, on-body inertial sensors, clothing-integrated textile elongation sensors, and visual tracking, all give information about body parts trajectories. If the classifiers are trained on such trajectories rather than on raw sensor signals, then the classification ...

The classical interpretation of probability together with the Principle of Indifference are formulated in terms of probability measure spaces in which the probability is given by the Haar measure. A notion called Labeling Irrelevance is defined in the category of Haar probability spaces, it is shown that Labeling Irrelevance is violated and Bertrand’s Paradox is interpreted as the very proof of...

We propose to develop a formal model of information representation and processing in the part of the neocortex that is mostly concerned with visual information. This model will open new horizons in a well-principled way in the fields of artificial and biological vision as well as in computational neuroscience. Specifically the goal is to develop a universally accepted formal framework for descr...