By Andrew Blake
Active Contours offers with the research of relocating photographs - an issue of starting to be significance in the special effects undefined. particularly it really is inquisitive about figuring out, specifying and studying past types of various energy and making use of them to dynamic contours. Its objective is to improve and examine those modelling instruments intensive and inside a constant framework.
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Additional resources for Active Contours: The Application of Techniques from Graphics, Vision, Control Theory and Statistics to Visual Tracking of Shapes in Motion
Snakes are a mechanism for bringing a certain degree of prior knowledge to bear on low-level image interpretation. Rather than expecting desirable properties such as continuity and smoothness to emerge from image data, those properties are imposed from the start. Specifically, an elastic model of a continuous, flexible curve is imposed upon and matched to an image. By varying elastic parameters, the strength of prior assumptions can be controlled. Prior modelling can be made more specific by constructing assemblies of flexible curves in which a set of parameters controls kinematic variables, for instance the sizes of various subparts and the angles of hinges which join them.
A regular snake, with suitably chosen internal energy may succeed in tracking several dozen frames off-line. However, once tracking is seen as a continuous process, and this is the viewpoint that real-time experiments enforce, the required standards of robustness are altogether more stringent. What was an occasional failure in one computation out of every few. becomes virtually certain eventual failure once the real-time process is allowed to run. It is of paramount importance that recovery from transients - such as a gust of wind causing the leaf 32 Chapter 2 to twitch - is robust.
Much effort was directed towards finding significant features in images. , 1977) on grouping them into linear structures. See also (Ballard and Brown, 1982) for a broad review. The challenge lies in recovering features undamaged and free of breaks, and in successfully grouping them according to the object to which they belong. In some cases subsequent processes can tolerate errors - gaps in contours and spurious fragments - and this is particularly true of certain approaches to object recognition, for instance (Ballard, 1981; Grimson and Lozano-Perez, 1984; Faugeras and Hebert, 1986; Mundy and Heller, 1990).
Active Contours: The Application of Techniques from Graphics, Vision, Control Theory and Statistics to Visual Tracking of Shapes in Motion by Andrew Blake