Panoramic video capturing and compressed domain virtual camera control

Xinding Sun, J. Foote, Don Kimber, B. S. Manjunath
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引用次数: 37

Abstract

A system for capturing panoramic video and a novel method for corresponding compressed domain virtual camera control is presented. It targets applications such as classroom lectures and video conferencing. The proposed method is based on the FlyCam panoramic video system that is designed to produce high resolution and wide-angle video sequences by stitching the video pictures from multiple stationary cameras. The panoramic video sequence is compressed into an MPEG-2 stream for delivery. The proposed method integrates region of Interest (ROI) detection, tracking, and virtual camera control, and works on compressed domain information only. It first detects the ROI in the P (predictive coded) picture using only the macroblock type information, It then up-samples this detection result to obtain the ROI of the whole video stream. The ROI is tracked using a Kalman filter. The Kalman filter estimation results are used for virtual camera control that simulates human controlled video recording. The system has no physical camera motion and the virtual camera parameters are readily available for video indexing. The proposed system has been implemented for real time processing.
全景视频捕获与压缩域虚拟摄像机控制
提出了一种全景视频采集系统和相应的压缩域虚拟摄像机控制方法。它针对的是课堂讲座和视频会议等应用。该方法基于FlyCam全景视频系统,该系统旨在通过拼接多台固定摄像机的视频图像来产生高分辨率和广角视频序列。全景视频序列被压缩成MPEG-2流进行传输。该方法集成了感兴趣区域(ROI)检测、跟踪和虚拟摄像机控制,并且只处理压缩域信息。它首先只使用宏块类型信息检测P(预测编码)图像中的ROI,然后对该检测结果进行上采样以获得整个视频流的ROI。使用卡尔曼滤波器跟踪ROI。将卡尔曼滤波估计结果用于模拟人控录像的虚拟摄像机控制。该系统没有物理摄像机运动,虚拟摄像机参数可以方便地用于视频索引。该系统已用于实时处理。
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