Towards Object Recognition using HDR Video, Stereoscopic Depth Information and SIFT

We present an approach to object detection and recognition in a digital image using a classification method that is based on the application of a set of features that include

We have presented some validation methods for identify- ing the quality of the expansion methods. These validation methods currently only cater for still images and IBL appli-

We present a novel method for High Dynamic Range video where the critical phases of the pipeline are based on histograms.. It is possible to achieve high framerates, since the

It is backward compatible with LDR stereo JPEG but not fully compatible with JPEG-HDR and traditional JPEG; the image shown on a traditional JPEG viewer would be both images side

Two different editing problems are approached: First, the removal of ghosting artifacts from high dynamic range (HDR) images recovered from exposure sequences, and sec- ond, the

We named this perception “stereoscopic pseudo-transparency.” Our experiments investigated (1) the effectiveness of the proposed method in improving the depth perception

High dynamic range (HDR) video technology has gone through remarkable developments over the last few years; HDR-video cameras are being commercialized, new algorithms for color

Jonas Unger’s research interests lie at the intersec- tion of computer graphics and image processing, where he is currently driving projects directed towards High Dynamic Range