2 research outputs found
Caricature generator
Thesis (M.S.V.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1982.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH.Bibliography: leaves 111-116.The human face is a highly significant visual display which we are able to remember and recognize easily despite the fact that we are exposed to thousands of faces which may be metrically very similar. caricature is a graphical coding of facial features which seeks to be more like the face than the face itself: selected information is exaggerated, noise is reduced, and the processes involved in recognition are exploited. After studying the methods of caricaturists, examining perceptual phenomena regarding individuating features, and surveying automatic and man-machine systems which represent and manipulate the face, some heuristics for caricature are defined . An algorithm is implemented to amplify the nuance of a human face in a computer- generated caricature. This is done by comparing the face to a norm and then distorting the face even further away from that norm . Issues of style, context and animation are discussed. The applications of the caricature generator in the areas of teleconferencing, games, and interactive graphic interfaces are explored.by Susan Elise Brennan.M.S.V.S
Recommended from our members
Visual recognition of objects : behavioral, computational, and neurobiological aspects
I surveyed work on visual object recognition and perception. In animals, vision has been studied mainly on the behavioral and neurobiological levels. Behavioral data typically show what the visual system, by itself or together with the rest of the organism, is capable of. They show, for example, that humans can recognie objects regardless of size and position, but that rotated objects pose problems. Important insights into the organization of behavior have also been provided by people who suffered localized brain damage. We have learned that the brain is divided into areas subserving different and relatively well-defined behaviors. The visual system itself is also organized in different subsystems; the visual cortex alone contains nearly twenty maps of the visual field. And individual neurons respond selectively to visual stimuli, e.g., the orientation of line segments, color, direction of motion, and, most intriguingly, faces. The question is how the actions of all these neurons produce the behavior we observe. How do neurons represent the shape of objects such that they can be recognized? Before we can answer the question, we have to understand the computational aspect of shape representation, the nature of the problem as it were. Many methods for representing shape have been explored, mainly by computer scientists, but so far no satisfactory answers have been found