Scalable Parallel Module for Capturing Multiple Video Streams in Real Time

Abstract

The process of capturing multiple IP video streams in real time is of great importance for the development of heterogeneous computer vision systems, because it is the first stage for the management of various processes that base their potential on visual analysis for decision making in different organizational environments. This process demands the execution of a high number of operations that guarantees that several concurrent video streams are managed without losses and under time restrictive conditions. In this sense, a parallel and scalable software module has been designed to optimize the use of computational resources in order to capture a higher number of concurrent video streams. The parallel algorithm is based on shared-distributed memory programming paradigms and improves the efficiency of the use of the network adapters architecture and integrates the potential of all the processing cores available in the computational node that supports the process, based on the cooperation between processors and computational nodes on a high-performance computational infrastructure with the purpose of promoting the scalability of the system. It is important to point out that the video capture module has transversal applicability in several application domains and makes it possible to increase the number of video streams to be processed concurrently in correspondence with the available hardware architecture.