VisualisingVideo Sequences usingDirect Volume Rendering

نویسندگان

  • Gareth Daniel
  • Min Chen
چکیده

It is evident that more and more video data is being generated everyday, for example, by TV broadcast companies and security cameras. However, whilst we are overwhelmed by the huge amount of imagery data, machine vision is generally not yet ready to replace us in most of the everyday visual tasks. In this paper we present a novel approach to the handling of video data. We propose to employ volume visualisation techniques for “summarising” video sequences, and to render video volumes into appropriate visual representations. Such visualisations can be used to assist in a decision making process, for instance, to determine if there is any unusual level of activity recorded in a video. In the paper, we present a prototype system, called V3, for capturing, managing, processing and visualising video data sets. We highlight the conceptual similarity between video visualisation and the traditional volume visualisation, and describe the deployment of conventional transfer functions and spatial transfer functions in video visualisation. We examine several statistical image comparison metrics and discuss their effectiveness in extracting meaningful information from video sequences. This work demonstrates the importance and the potential of combining graphics, video and vision technologies.

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تاریخ انتشار 2003