Efficient implementation and processing of a real-time panorama video pipeline with emphasis on dynamic stitching

The Bagadus system has been introduced as an automated tool for soccer analysis, and it is built up by an analysis subsystem, tracking subsystem and video subsystem. Bagadus allows for simplified soccer analysis, with the goal of improving athletes' performance, by automating the integration of these subsystems. The system is currently installed at Alfheim stadium in Tromsø, Norway. An important part of the video subsystem is the creation of panorama videos from four HD cameras. However, the stitching pipeline for panorama video generation in the first version of the system did not manage to do this in real-time. In this thesis, we present how to build an improved panorama stitcher pipeline that is able to stitch video from four HD cameras into a panorama video in real-time. We will detail the architecture and modules of this pipeline, and analyze the performance. In addition we will focus on the stitching component, and how that can improve the overall visual quality of the output panorama

Efficient Implementation and Processing of a Real-Time Panorama Video Pipeline

Abstract—High resolution, wide field of view video generated from multiple camera feeds has many use cases. However, processing the different steps of a panorama video pipeline in real-time is challenging due to the high data rates and the stringent requirements of timeliness. We use panorama video in a sport analysis system where video events must be generated in real-time. In this respect, we present a system for real-time panorama video generation from an array of low-cost CCD HD video cameras. We describe how we have implemented different components and evaluated alternatives. We also present performance results with and without co-processors like graphics processing units (GPUs), and we evaluate each individual component and show how the entire pipeline is able to run in real-time on commodity hardware. I