A method for the reconstruction of 3D shape and texture from integral photography (IP) images is presented. Sharing the same principles with stereoscopic-based object reconstruction, it offers increased robustness to noise and occlusions due to the unique characteristics of IP images. A coarse-to-fine approach is used, employing what we believe to be a novel grid refinement step in order to increase the quality of the reconstructed objects. The proposed method's properties include configurable depth accuracy and direct and seamless triangulation. We evaluate our method using synthetic data from a computer-simulated IP setup as well as real data from a simple yet effective digital IP setup. Experiments show reconstructed objects of high-quality indicating that IP can be a competitive modality for 3D object reconstruction.
Integral imaging is one of the most promising techniques for delivering three-dimensional content. Most processing tasks usually require prior knowledge of the size and positions of the elemental images that comprise an integral image. In this paper we propose an automated method for calibrating the acquisition setup, by applying a preprocessing stage to an acquired integral image. The skew angle is extracted and the size and positions of the elemental images are accurately determined. For these purposes a method is developed to automatically identify an elemental image lattice that best matches the acquired integral image.
One of the most promising techniques for visualizing three-dimensional objects is Integral Photography (IP). Two of the most common methods used in Computer Generated IP involve the development of simplified ray tracing algorithms for elementary 3D objects or the realization of pinhole arrays. We present an alternative technique based on the POV-Ray software package for ray tracing to generate synthetic, high quality and photorealistic integral images, by accurately modeling all the optical elements of the capturing setup. Our work constitutes a straightforward approach for translating a computer generated 3D model to an IP image and a robust method to develop modules that can be easily integrated in existing ray-tracers. The proposed technique simulates the procedure of a single stage IP capture for producing orthoscopic IP images, real or virtual. Full control is provided over geometry selection, size and refractive index of the elementary microlenses. Specifically our efforts have been focused on the development of arrays with different geometries (square or hexagonal) that demonstrates the parameterization capabilities of the proposed IP setup. Moreover detailed benchmarking is provided over a variety of sizes and geometries of microlens arrays.
Abstract. Integral Imaging is a highly promising technique for delivering full parallax autostereoscopic images. A straight-forward approach for producing high quality photorealistic Integral Images or Integral Image sequences is the use of Ray-Tracing techniques. However, Ray-Tracing tasks are time consuming and in most cases scene renderings greatly deviate from performing in real time. In this work, we describe an Integral Image specific benchmarking procedure that allows accurate rendering performance evaluation of different parts of the Ray-Tracing process. A correlation based method is used to characterize the Integral Image complexity and finally calculate its actual complexity. Moreover, a number of issues are exposed that should be taken into account in realtime Integral Imaging applications.
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