We have developed a reliable and practical HD stereoscopic camera system. It consists of a pair of full digital boxtype HD video camera, small radius SD class lens, a multiplexer board and some other control boards. The camera is a parallel-axes style. We control the convergence by moving the lens slightly inward which is separated from the camera body. We have used two sets of linear motor modules to control the convergence and the distance between the two cameras precisely. The various camera parameters concerned with stereoscopic view can be displayed in the viewfinder, stored with video and used for studying picture quality improvement and assessment. We have combined zoom control with convergence control for the convenience of stereoscopic image capturing, so we can control them with one knob.They also can be controlled individually. The built-in multiplexer board receives two video signals from the left and right camera, and makes them into one side-by-side image that is compressed in half horizontally and multiplexed two images.After this process we can record the video into a normal VCR, then reconstruct the original two images by demultiplexer, and we can enjoy stereoscopic images.
Real-time virtual studios which could run only on expensive workstations are now available for personal computers thanks to the recent development of graphics hardware. Nevertheless, graphics are rendered off-line in the post production stage in film or TV drama productions, because the graphics' quality is still restricted by the real-time hardware. Software-based camera tracking methods taking only the source video into account take much computation time, and often shows unstable results. To overcome this restriction, we propose a system that stores camera motion data from sensors at shooting time as common virtual studios and uses them in the post production stage, named as POVIS(post virtual imaging system). For seamless registration of graphics onto the camera video, precise zoom lens calibration must precede the post production. A practical method using only two planar patterns is used in this work. We present a method to reduce the camera sensor's error due to the mechanical mismatch, using the Kalman filter. POVIS was successfully used to track the camera in a documentary production and saved much of the processing time, while conventional methods failed due to lack of features to track.
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