Abstract :
Video data, generated by the entertainment industry, security and traffic cameras, video conferencing systems, video emails, and so on, is perhaps most time-consuming to process by human beings. In this paper, we present a novel methodology for "summarizing" video sequences using volume visualization techniques. We outline a system pipeline for capturing videos, extracting features, volume rendering video and feature data, and creating video visualization. We discuss a collection of image comparison metrics, including the linear dependence detector, for constructing "relative" and "absolute" difference volumes that represent the magnitude of variation between video frames. We describe the use of a few volume visualization techniques, including volume scene graphs and spatial transfer functions, for creating video visualization. In particular, we present a stream-based technique for processing and directly rendering video data in real time. With the aid of several examples, we demonstrate the effectiveness of using video visualization to convey meaningful information contained in video sequences.
Keywords :
data visualisation; image sequences; video signal processing; image comparison metrics; linear dependence detector; security camera; spatial transfer technique; stream-based technique; traffic camera; video capturing; video conferencing system; video data; video email; video processing; video rendering; video sequences; video visualization; volume rendering video; volume scene graph; volume visualization; Cameras; Data mining; Data security; Data visualization; Feature extraction; Humans; Pipelines; Rendering (computer graphics); Video sequences; Videoconference;
