We describe a video surveillance system that detects abandoned packages automatically. In this system, multiple cameras locate objects in space and time despite occlusions and distracting lighting effects observed by subsets of the cameras. A multiple-state model of an abandoned package provides the ability to detect realistic abandoned package events. The paper outlines the system by describing the modules for camera view segmentation, object classification, view-object association, 3D object tracking, and finally detection of the event of a package being abandoned, which highlights object association using multiple cameras and the multiple-state abandoned package model.

We present the design and implementation of the Virtual Microscope, a software system employing a client/server architecture to provide a realistic emulation of a high power light microscope. The system provides a form of completely digital telepathology, allowing simultaneous access to archived digital slide images by multiple clients. The main problem the system targets is storing and processing the extremely large quantities of data required to represent a collection of slides. The Virtual Microscope client software runs on the end user's PC or workstation, while database software for storing, retrieving and processing the microscope image data runs on a parallel computer or on a set of workstations at one or more potentially remote sites. We have designed and implemented two versions of the data server software. One implementation is a customization of a database system framework that is optimized for a tightly coupled parallel machine with attached local disks. The second implementation is component-based, and has been designed to accommodate access to and processing of data in a distributed, heterogeneous environment. We also have developed caching client software, implemented in Java, to achieve good response time and portability across different computer platforms. The performance results presented show that the Virtual Microscope systems scales well, so that many clients can be adequately serviced by an appropriately configured data server.

We show how five low-cost and nonintrusive techniques that work using free commodity tools such as GDB can be used to improve the debugging process of multi-threaded and/or distributed parallel programs. These techniques have been used in the development of major software middleware - DataCutter and MQO - and have proven their value by lowering the time necessary to detect and correct bugs.

Processing of data in many data analysis applications can be represented as an acyclic, coarse grain data flow, from data sources to the client. This paper is concerned with scheduling of multiple data analysis operations, each of which is represented as a pipelined chain of processing on data. We define the scheduling problem for effectively placing components onto Grid resources, and propose two scheduling algorithms. Experimental results are presented using a visualization application.

Research on programming models for developing applications in the Grid has proposed component-based models as a viable approach, in which an application is composed of multiple interacting computational objects. We have been developing a framework, called filter-stream programming, for building data-intensive applications that query, analyze and manipulate very large data sets in a distributed environment. In this model, the processing structure of an application is represented as a set of processing units, referred to as filters. We develop the problem of scheduling instances of a filter group. A filter group is a set of filters collectively performing a computation for an application. In particular we seek the answer to the following question: should a new instance be created, or an existing one reused? We experimentally investigate the effects of instantiating multiple filter groups on performance under varying application characteristics.

Large client-server data intensive applications can place high demands on system and network resources.This is especially true when the connection between the client and server spans a widearea intemet link.In this paper, we describe our experience changing the typical client-server architecture for a class of data intensive applications.We show that given sufficient common interest among multiple clients, our enhancements reduce the response time per-client, the response-time variation and the amount of data sent across the wide-area link.In addition, we also see a reduction in server utilization which helps to improve server scalability.