RPV-II: A Stream-Based Real-Time Parallel Vision System and Its Application to Real-Time Volume Reconstruction

Abstract

In this paper, we present RPV-II, a stream-based real-time parallel image processing environment on distributed parallel computers, or PC-cluster, and its performance evaluation using a realistic application. The system is based on our previous PC-cluster system for real-time image processing and computer vision, and is designed to overcome the problems of our previous system, one of which is long latency when we use pipelined structures. This becomes a serious problem when we apply the system to interactive applications. To make the latency shorter, we have introduced stream data transfer, or fine grained data transfer, to RPV-II. One frame data is divided into small elements such as pixels, lines and voxels, and we have developed efficient real-time data transfer mechanism of those. Using RPV-II we have developed a real-time volume reconstruction system by visual volume intersection method, and we have measured the system performance. Experimental results show better performance than that of our previous system, RPV.KeywordsVisual ConeFrame PeriodPipeline StructureVoxel SpaceData Processing ModuleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.