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High-Order Luminance Modeling for 3-D Model-Based Coding of ...

High-Order Luminance Modeling for 3-D Model-Based Coding of ...

High-Order Luminance Modeling for 3-D Model-Based Coding of

High-Order Luminance Modeling for 3-D Model-Based Coding of Multiview Image Sequences Nikos Grammalidis and Michael G.Strintzis Department of Electrical Engineering University of Thessaloniki Thessaloniki 540 06, GREECE ABSTRACT An interframe coding method for multiview image sequences using 3-D models is presented. The 3-D motion is estimated using an optical ow formulation which also takes into consideration the photometric eects of rotation, using a specular illumination reection model. More specically, the Phong specular reection model is used, resulting to a luminance model which depends on the surface normal at each 3-D point, six illumination parameters, as well as the viewing angle. A Gauss-Newton optimization technique is used to estimate the illumination parameters. During the motion estimation stage, the same technique is used to estimate the 3-D motion parameters. Experimental results show that the use of this illumination model for motion compensation results in improved image reconstruction, when compared to standard 2-D and 3-D motion estimation techniques. 1. INTRODUCTION Recently, use of various illumination models has been proposed to achieve shape extraction and improved motion compensation [1, 2]. In [3], a diuse light reection model is used to estimate illumination and 3-D motion parameters using a non-diuse illumination model. This illumination and motion estimation and compensation scheme is then intergrated into an Object Based Analysis - Synthesis Coder (OBASC) [4]. In this paper, we propose the use of Phong's specular reection model for improved motion estimation and compensation. This motion estimation and compensation technique is then applied for interframe coding using all views of the multiview image sequence. This work was supported by the European Commission project ACTS 092: PANORAMA 2. DEPTH AND ILLUMINATION ESTIMATION In order to apply the proposed technique, a wireframe model of the objects in the scene has to be provided. For this reason, we have chosen to use the depth estimation method from trinocular image sequences proposed in [5], which is particularly useful for the segmentation, as well as the modeling phases. An advantage of depthbased segmentation is that it provides good results even for scenes containing complex backgrounds. A wireframe R of 3-D points may then obtained from the estimated depth maps, provided that the camera geometry is known. While any wireframe R may beusedtoapply the proposed interframe coding technique, we have examined the use of very coarse wireframe models, like an ellipsoid model to describe the human head and a planar depth model to describe the rest of the human body. More specically,we assume a typical videoconferencing scene, i.e. a person in front ofthecameras, and that the background of the scene has been extracted, e.g. using the estimated depth information or motion detection techniques. The center and axes of the best-tting ellipsoid to the subset R h of R describing the \head" area are then found using Principal Component Analysis. Using this procedure, we obtain a coarse description of the shape of the human head using just 9 oating point parameters : the ellipsoid center (c x c y c z ), the lengths (l x l y l z ) of the ellipsoid axes and the three angles between the major axes of the ellipsoid and the axes of the world coordinate system. Despite its simplicity, this \full 3-D" model, as opposed to a \2 1/2- D" model, is advantageous especially in order to handle occlusions occurring between two consecutive time instants, when more than one view is available. After the shape estimation stage, the illumination of the scene is estimated, based on a few

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