Abstract
To tackle the growing complexity and huge demand for tailored domestic video surveillance systems along with a high demanding time-to-market expectation, engineers at IVV Automação, LDAa are exploiting video surveillance domain as families of systems that can be developed following a pay-as-you-go fashion rather than developing an ex-nihilo new product. Several and different new functionalities are required for each new product’s hardware platforms (e.g., ranging from mobile phone, PDA to desktop PC) and operating systems (e.g., flavors of Linux, Windows and MAC OS X). Some of these functionalities have special economical constraints of development time and memory footprint. To better accommodate all the above listing requirements, a model-driven generative software development paradigm supported by mainstream tools is proposed to offer a significant leverage in hiding commonalities and configuring variabilities across families of video surveillance products while maintaining the new product quality.
Highlights
Nowadays there is a growing demand for video surveillance systems [1]
It can be noticed that the increasing complexity is induced by the variability in tasks related to image capturing, image processing, communications and computer vision [3]
DirectShow is a pipeline-based media-streaming architecture and API based on component object model (COM) framework that provides a common interface for media across several programming languages
Summary
Nowadays there is a growing demand for video surveillance systems [1]. The development of these systems is increasingly complex since there is a high demand for new products with a rising number of different requirements [2]. The majority of system designers use modular architectures based on Microsoft DirectShow implementation [4,5] in order to address the growing complexity of novel products and the ever increasing time-to-market pressure. In this implementation, all system functionalities are implemented as individual plug-ins or filters. It describes how offline and online partial evaluators [13] will be applied, respectively, at whole system and filter designs. A layered architecture, called GenVoca is used and the configuration knowledge is implemented using C++ template metaprogramming as generator
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