SHADING INTO TEXTURE

AAAI Conferences

Alex P. Pentland Artificial Intelligence Center, SRI International 333 Ravenswood Ave., Menlo Park, California 94025 ABSTRACT Shape-from-shading and shape-from-texture methods have the To accomplish this, we must have rccour8e to a 3-D model competent to describe both crumpled surface8 and smooth ones. The fractal model of surface shape [6,7] appears to possess the required properties. Evidence for this comes from recently conducted surveys of natural imagery [6,8]. These survey found that the fractal model of imaged 3-D surfaces furnishes an accurate description of most textured and shaded image regions. Perhaps even more convincing, however, is the fact that fractals look like natural surfaces [9,10,11].


The Fractal Nature of the Semantic Web

AI Magazine

In the past, many knowledge representation systems failed because they were too monolithic and didn't scale well, whereas other systems failed to have an impact because they were small and isolated. Along with this trade-off in size, there is also a constant tension between the cost involved in building a larger community that can interoperate through common terms and the cost of the lack of interoperability. Its main contribution is in recognizing and supporting the fractal patterns of scalable web systems. In this article we discuss why fractal patterns are an appropriate model for web systems and how semantic web technologies can be used to design scalable and interoperable systems.


The Real Secret of Youth Is Complexity - Issue 36: Aging

Nautilus

Saint Thomas Aquinas preached that simplicity brings one closer to God. Isaac Newton believed it leads to truth. The process of simplification, we're told, can illuminate beauty, strip away needless clutter and stress, and help us focus on what really matters. It can also be a sign of aging. Youthful health and vigor depend, in many ways, on complexity.


The Real Secret of Youth Is Complexity - Issue 68: Context

Nautilus

Saint Thomas Aquinas preached that simplicity brings one closer to God. Isaac Newton believed it leads to truth. The process of simplification, we're told, can illuminate beauty, strip away needless clutter and stress, and help us focus on what really matters. It can also be a sign of aging. Youthful health and vigor depend, in many ways, on complexity.


Estimating the intrinsic dimension in fMRI space via dataset fractal analysis - Counting the `cpu cores' of the human brain

arXiv.org Machine Learning

Functional Magnetic Resonance Imaging (fMRI) is a powerful non-invasive tool for localizing and analyzing brain activity. This study focuses on one very important aspect of the functional properties of human brain, specifically the estimation of the level of parallelism when performing complex cognitive tasks. Using fMRI as the main modality, the human brain activity is investigated through a purely data-driven signal processing and dimensionality analysis approach. Specifically, the fMRI signal is treated as a multi-dimensional data space and its intrinsic `complexity' is studied via dataset fractal analysis and blind-source separation (BSS) methods. One simulated and two real fMRI datasets are used in combination with Independent Component Analysis (ICA) and fractal analysis for estimating the intrinsic (true) dimensionality, in order to provide data-driven experimental evidence on the number of independent brain processes that run in parallel when visual or visuo-motor tasks are performed. Although this number is can not be defined as a strict threshold but rather as a continuous range, when a specific activation level is defined, a corresponding number of parallel processes or the casual equivalent of `cpu cores' can be detected in normal human brain activity.