Abstract. This paper presents a computational model that segments images based on the textural properties of object surfaces. The proposed Coupled-Membrane model applies the weak membrane approach to an image Wl(O ' derived from the power responses of a family of selfsimilar quadrature Gabor wavelets. While segmentation breaks are allowed in x and y only, coupling is introduced to in all 4 dimensions. The resulting spatial and spectral diffusion prevents minor variations in local textures from producing segmentation boundaries. Experiments showed that the model is adequate in segmenting a class of synthetic and natural texture images. 1

Issues of representation arise in natural language processing, user interface design, art, and indeed, communication with any medium. This paper addresses such issues using algebraic semiotics, which draws on algebraic speci cation to give (among other things) an algebraic theory of representation, and a generalization of blending in the sense of cognitive linguistics.

This paper has not already been accepted by and is not currently under review for a journal or another conference. Nor will it be submitted for such during the IJCAI's review period

This thesis presents a computational framework for the automatic recognition and prediction of different kinds of human behaviors from video cameras and other sensors, via perceptually intelligent systems that automatically sense and correctly classify human behaviors, by means of Machine Perception and Machine Learning techniques. In the thesis I develop the statistical machine learning algorithms (dynamic graphical models) necessary for detecting and recognizing individual and interactive behaviors. In the case of the interactions two Hidden Markov Models (HMMs) are coupled in a novel architecture called Coupled Hidden Markov Models (CHMMs) that explicitly captures the interactions between them. The algorithms for learning the parameters from data as well as for doing inference with those models are developed and described. Four systems that experimentally evaluate the proposed paradigm are presented: (1) LAFTER, an automatic face detection and tracking system with facial expression recognition; (2) a Tai-Chi gesture recognition system; (3) a pedestrian surveillance system that recognizes typical human to human interactions; (4) and a SmartCar for driver maneuver recognition. These systems capture human behaviors of different nature and increasing complexity: first, isolated, single-user facial expressions, then, two-hand gestures and human-to-human interactions,...

Abstract not found

Abstract. If co-operating government agencies reside in different countries, they will differ in many respects: administrative ontologies and laws, political context, administrative culture, and computing infrastructure. Inter-organizational e-government services may provide technical interoperability, but do not necessarily solve the problem how to understand a foreign administration. In this paper, we shall discuss the difficulties of citizens in dealing with heterogeneous local e-government services. 1

Various defenses of amodal symbol systems are addressed, including amodal symbols in sensory-motor areas, the causal theory of concepts, supramodal concepts, latent semantic analysis, and abstracted amodal symbols. Various aspects of perceptual symbol systems are clarified and developed, including perception, features, simulators, category structure, frames, analogy, introspection, situated action, and development. Particular attention is given to abstract concepts, language, and computational mechanisms.

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statistics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement recording systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The storage and reactivation of perceptual symbols operates at the level of perceptual components -- not at the level of holistic perceptual experiences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a common frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspection (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and abstract concepts, thereby implementing a fully functional conceptual sy...

The developments in behavior-based robotics and in ecological psychology have had a strong effect on theoretical development in some research communities. A new belief has emerged under the name of antirepresentationalism, which is strongly opposed to the notion of representations in cognition. This notion is spurred by the inarguably fruitful insight that behavioral complexity can be brought about by simple mechanisms at a low systemic level. Although there are many problems with constructed formal representations in the toy models of traditional artificial intelligence, there is a fundamental problem with extreme anti-representationalism, as well. Representations actually do exist in the biological neural-information processing system. In this paper, a review of neural representation mechanisms will be given, looking at perception and motor control in biological systems. Subsequently, it will be illustrated that already in simple animal behaviors, simple 'representation-less' reactivity does not suffice. Anticipation exists even in jumping spiders, requiring the existence of a representation as the computational basis for the prediction of future system states.

ii iii CAROLINE ZIEMKIEWICZ. Understanding the Structure of Information Visualization Through Visual Metaphors. (Under the direction of DR. ROBERT KOSARA) Information visualization is an increasingly widespread way to present and analyze complex data, but there is much we still do not know about how people understand visually presented information. Every visualization contains certain assumptions about the structure of its information: how the data can be broken down into pieces, how those pieces relate to one another, what actions can and cannot be performed with the data, and so forth. Yet information visualization still lacks the language and theory to analyze these properties of visual information structure. I propose that these structural properties can be thought of as visual metaphors that drive a visualization, analogous to the verbal metaphors that structure abstract information in speech and writing. In this model, people analyze visual relationships among shapes and patterns