In this paper, we propose an image-based technique for panoramic novelview generation using three uncalibrated wide-angle images as its input. State of the art in novel view generation presumes the calibration and removal of radial distortion or any other deformation resulting from t he geometry of a non-central camera. We propose a method which replaces this calibration with the assumption that the epipole corresponding to the novel viewpoint is at the center of radial distortion and that it is known. 1 Introduction In novel view synthesis, given an image pair, the intensity of each ray in the novel view is determined by finding corresponding point matches betwee n those images, using the epipolar geometries between the two views and with respect to the novel view. This process requires that the given images obey the standard perspective model, with a single viewpoint and no radial distortion. Such assumptions make the creation of novel panoramas a process of acquiring tens of images, each with relatively narrow field-of-view, with special apparatus, and applying calibration and estimatio n of circular motion [9]. In this paper, we propose an approach where a novel view can be synthesized from multiple views which might be highly radially distorted, and even non-central, without compensating explicitly for the resulting image deformations. We shed new light on the problem (Fig. 1) of “how a scene looks from a scene point?”[8] by eliminating the need for a reference plane and facilitating synthesis of omnidre ctional novel views. We assume that, for n ≥ 3 views, the location of the epipole of the novel view in each image is known, and, in the case of radially distorted views, that it is coincident with the centre of radial distortion in the image. This assumption is either enforced (for example by choosing a visible scene point as the centre of projection of the view to be synthesized, and actually fixating on this point in the case of radially dis torted views), or else it may naturally be satisfied for certain wide-angle imaging syste ms (for example multiple views of a spherical mirror). Given such a configuration, the 2D sta r of virtual rays at the novel viewpoint are mapped to a 1D star of lines in each image, which we model as a projection from P 2 (the domain of the novel view) to P 1 (the angles of the line pencil in image plane). We make use of the well known fact that three projections of a line in space (a virtual line in our case) yield a trifocal constraint, from w hich we extract the projection matrices required for the view synthesis. The main contributions of this paper are:

The automated detection of humans in computer vision as well as the realistic rendering of people in computer graphics necessitates improved modeling of the human skin color. We describe the acquisition and modeling of skin reflectance data densely sampled over the entire visible spectrum. The data collected through a spectrograph allows us to explain skin color (and its variations) and to discriminate between human skin and dyes designed to mimic human skin. We study the approximation of these data using several sets of basis functions. Our study shows that skin reflectance data can best be approximated by a linear combination of Gaussians or their first derivatives. This result has a significant practical impact on optical acquisition devices: the entire visible spectrum of skin reflectance can now be captured with a few filters of optimally chosen central wavelengths and bandwidth.