Sparse acquisition integral imaging system
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(College of Communication Engineering, Jilin University, Changchun 130012, China)

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TP751.1;TP751.2

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    Abstract:

    Using 3DS MAX to obtain elemental image (EI) array in the virtual integral imaging system need to put large-scale camera array which is difficult to be applied to practice. To solve this problem we establish a sparse acquisition integral imaging system. In order to improve the accuracy of disparity calculation, a method is proposed using color segmentation and integral projection to calculate the average disparity value of each color object between two adjacent render output pictures. First, a virtual scene and micro lens array model in 3DS MAX is established. According to the mapping relationship between EI and sub image (SI), we can obtain the SI first, and then calculate the EI. Based on color image segmentation method and integral projection method, we acquire the average value of the disparity from different color objects between adjacent images; and then translate a rectangular window of fixed size in accordance with the average disparity to intercept rendering images to get the sub images. Finally, after stitching and mapping of the sub images we obtain the elemental images, which can be used to display a 3-dimentioanal (3D) scene. The experimental results show that we can use only 12×12 cameras instead of 59×41 cameras to obtain elemental images, and the stereoscopic display effect is obvious. The error rate of disparity computation is 0.433% in both horizontal and vertical directions, which is obviously better than other methods of disparity error rate of 2.597% and 4.762%. The sparse acquisition integral imaging system is more accurate and more convenient which can be used for EI content acquisition for large screen stereoscopic display.

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History
  • Received:May 05,2017
  • Revised:
  • Adopted:
  • Online: April 27,2018
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