as regular (finite state) processes that provide guarantees of service along public channels. We also propose a new notion of subtyping for active objects, based on Brinksma's notion of extension, that extends Wegner and Zdonik's "principle of substitutability" to non-uniform service

This paper describes the Active Object pattern, which decouples method execution from method invocation in order to simplify synchronized access to an object that resides in its own thread of control. The Active Object pattern allows one or more independent threads of execution to interleave

A novel scheme for the detection of object boundaries is presented. The technique is based on active contours evolving in time according to intrinsic geometric measures of the image. The evolving contours naturally split and merge, allowing the simultaneous detection of several objects and both

In this paper, we propose a new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford--Shah functional for segmentation and level sets. Our model can detect objects whose boundaries are not necessarily defined by gradient. We minimize

curve need no longer be close to the solution to converge. The curve passes over weak edges and is stopped only if the edge is strong. We give examples of extracting a ventricle in medical images. We have also made a first step toward 3D object reconstruction, by tracking the extracted contour on a

w4 is a real time visual surveillance system for detecting and tracking multiple people and monitoring their activities in an outdoor environment. It operates on monocular gray-scale video imagery, or on video imagery from an infrared camera. W4 employs a combination of shape analysis and tracking

Our goal is to develop a visual monitoring system that passively observes moving objects in a site and learns patterns of activity from those observations. For extended sites, the system will require multiple cameras. Thus, key elements of the system are motion tracking, camera coordination

Learning can be made more efficient if we can actively select particularly salient data points. Within a Bayesian learning framework, objective functions are discussed which measure the expected informativeness of candidate measurements. Three alternative specifications of what we want to gain

events are not detected by SAMOS, but users/applications have to notify the system about their occurrence by issuing an explicit raise operation. 2.2 Composite events The kinds of primitive events described above correspond to elementary occurrences and are not adequate for handling events that occur when some combination of other events happens. Thus, SAMOS supports composite events built from others by means of six event constructors. The disjunction of events (E1jE2) occurs when either E1 or E2 occurs. The conjunction of events (E1,E2) occurs when E1 and E2 occur, regardless of order. A sequence of events (E1;E2) occurs when first E1 and afterwards E2 occurs. The following three constructors monitor the occurrence of event instances of a specific event class during a predefined time interval. A composite event with the "*" -constructor (*E) will be signalled (and the corresponding rules will be executed) only once (after the first occurrence of E), even if the event E occurs sever...

For many KDD applications, such as detecting criminal activities in E-commerce, finding the rare instances or the outliers, can be more interesting than finding the common patterns. Existing work in outlier detection regards being an outlier as a binary property. In this paper, we contend