We propose a new method which compensates optical axes misalignment along with stereo camera zooming automatically. Optical axes misalignment is modeled as image sensor center translation from the lens center. To match the image points of left and right image, right camera translation and rotation equation is devised. By using these equations we can easily get the rig calibration value. Then, we can compensate optical axes misalignment by saving and applying this rig calibration information when we change the zoom of stereo camera. The explanation of the proposed method and devised equation will be provided. And experimental verification results using stereo camera rig will be presented in the paper.
We developed a new multi-view camera system composed of 9 cameras for capturing multi-view images and utilizing
them in research and exhibition. The system is composed of cameras, rig, convergence controller, LANC signal
controller, IEEE 1394 signal interface. And, we made a control program that can manage a record function and other
various camera parameters at PC. By this program, we can shoot multi-view scenes manipulating each element camera
independently or all 9 cameras totally. After the capturing, we transform the image into the glass-less multi-view display
format, and then we can enjoy natural multi-view images at lenticular display.
KEYWORDS: 3D image processing, Integral imaging, Image resolution, LCDs, 3D displays, Liquid crystals, 3D image reconstruction, Imaging arrays, 3D vision, Optical resolution
In this paper, we propose a resolution-enhanced integral imaging with pinhole arrays on liquid crystal (LC) panel. Since
light through a pinhole corresponds to a pixel in 3D image, we electrically move the pinhole arrays on LC panel fast
enough to make after-image effect and display corresponding elemental image synchronously without reducing the 3D
viewing aspect of the reconstructed image. The explanation of the proposed system will be provided and the
experimental results will also be presented.
KEYWORDS: Image segmentation, Cameras, Motion estimation, Image processing, Data acquisition, Image processing algorithms and systems, Video, Detection and tracking algorithms, 3D displays, 3D image processing
We present an algorithm for stereoscopic conversion of two-dimensional movie encoded in MPEG-2. The stereoscopic
algorithm consists of segmentation process and depth determination process. In the segmentation process, we segment
the image based on the dc information and the motion vector information encoded by MPEG-2. After the segmentation,
depth of each segment is determined by examining the motion vector and the overlapped region of the segment.
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