Defines and investigates fuzzy symmetric functions with don't‐care conditions and most‐unsymmetric functions. Represents and illustrates by examples algorithms for finding the grade of membership function and the number of most unsymmetric functions. Also presents applications to function representation, data reduction and error correction. The results may have useful applications to fuzzy logics, finding most‐unsymmetric images, fuzzy neural networks and related areas.
Facial primitives such as eyebrows, eyes and mouth are used for the computer estimation of emotion. Describes how a pictorial knowledge‐base and pictorial knowledge‐tree are constructed from facial primitives in order to identify emotions in humans. Shows how the pictorial knowledge is compiled using a rule‐based knowledge representation. Discusses the future research implications and suggests areas where such computer estimation may be applied.
IntroductionConventionally, Boolean algebra is introduced using the postulate-oriented approach. In this article, the lattice oriented approach is presented. It is shown that the relationships among sets, relations, lattices and Boolean algebra form a distributive but not complemented lattice. Illustrative examples are shown with corresponding Hasse diagrams. The results may have useful applications to chromosome classification, image sciences, fuzzy languages, fuzzy neural networks, a theory of usuality, cybernetic modelling, multivalued symmetric functions, and other related areas.
SUMMARYRecently, three-dimensional motion analysis and shape recovery have attracted growing attention as promising avenues of approach to image understanding, object reconstruction as well as computer vision for robotic Systems. The image generation problem and the model generation problem are presented. More specifically, the inputs to the image generator are an old image, object model, motion specification, and hidden line and hidden surface algorithms. The output is a new image. Since the object model is given, the top-down approach is usually used. On the other hand, for the model generation problem, the input is an image sequence while the output is an object model. Since the object model is not given, and bottom-up approach is usually used.In this paper, the largest possible object approach is proposed and the advantages of this approach are stated. They are:1. This approach may be applicable to objects with planar surfaces as well as nonplanar surfaces.2. This approach may be applicable to the case that there are more than one face change per frame.3. This approach may be applicable when the camera is moving.4. This approach may be applicable when the object is measured by several measuring stations.By using this approach, algorithms for simple object reconstruction given a sequence of pictures are presented together with illustrative examples. The relevance and importance of this work are discussed.The results of this paper may have useful applications in object reconstruction, pictorial data reduction and computer vision for robotic Systems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.