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http://dx.doi.org/10.3807/HKH.2009.20.2.094

Object-Based Integral Imaging Depth Extraction Using Segmentation  

Kang, Jin-Mo (School of Electrical Engineering, Seoul National University)
Jung, Jae-Hyun (School of Electrical Engineering, Seoul National University)
Lee, Byoung-Ho (School of Electrical Engineering, Seoul National University)
Park, Jae-Hyeung (School of Electrical & Computer Engineering, Chungbuk National University)
Publication Information
Korean Journal of Optics and Photonics / v.20, no.2, 2009 , pp. 94-101 More about this Journal
Abstract
A novel method for the reconstruction of 3D shape and texture from elemental images has been proposed. Using this method, we can estimate a full 3D polygonal model of objects with seamless triangulation. But in the triangulation process, all the objects are stitched. This generates phantom surfaces that bridge depth discontinuities between different objects. To solve this problem we need to connect points only within a single object. We adopt a segmentation process to this end. The entire process of the proposed method is as follows. First, the central pixel of each elemental image is computed to extract spatial position of objects by correspondence analysis. Second, the object points of central pixels from neighboring elemental images are projected onto a specific elemental image. Then, the center sub-image is segmented and each object is labeled. We used the normalized cut algorithm for segmentation of the center sub-image. To enhance the speed of segmentation we applied the watershed algorithm before the normalized cut. Using the segmentation results, the subdivision process is applied to pixels only within the same objects. The refined grid is filtered with median and Gaussian filters to improve reconstruction quality. Finally, each vertex is connected and an object-based triangular mesh is formed. We conducted experiments using real objects and verified our proposed method.
Keywords
Three-dimensional display; Integral imaging; Depth extraction; Normalized cut;
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