Sparse Acquisition Integral Imaging System

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 using color segmentation and integral projection to calculate the average disparity value of each color object between two adjacent images is proposed. Firstly, we need to finish the establishment of virtual scene and microlens array model in 3DS MAX. According to the mapping relationship between EI and sub image (SI), we can obtain the SI by first, then calculate to the EI. The average value of the disparity from different color objects between adjacent images is acquired based on color image segmentation method and integral projection method, and then translate a rectangular window of fixed size in accordance with the average disparities to intercept the rendered output images to get the sub images (SIs). Finally, after stitching and mapping of the SIs we obtain the elemental images (EIs), put the EIs into the display device to display 3-dimensional (3D) scene. The experimental results show that we can only use 12 * 12 cameras instead of 59 * 41 cameras to obtain EIs, and the 3D display effect is obvious. The error rate of disparity calculation is 0.433% in both horizontal and vertical directions, which is obviously better than other methods with 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 3D displaying.