GVI Group  Harvard University

Images harvested from the Web are proving to be useful for many visual tasks, including recognition, geo-location, and three-dimensional reconstruction. These images are captured under a variety of lighting conditions by consumer-level digital cameras, and these cameras have color processing pipelines that are diverse, complex, and scene dependent. As a result, the color information contained in these images is difficult to exploit. In this paper, we analyze the factors that contribute to the color output of a typical camera, and we explore the use of parametric models for relating these output colors to meaningful scenes properties. We evaluate these models using a database of registered images captured with varying camera models, camera settings, and lighting conditions. The database is available online at http://vision.middlebury.edu/color/.

@conference { 246, title = {An empircal camera model for internet color vision}, year = {2009}, month = {07/09/2009}, address = {London, UK}, author = {Ayan Chakrabarti and Daniel Scharstein and Todd Zickler} }