Surgical Guidance for Removal of Cholesteatoma Using a Multispectral 3D-Endoscope

We develop a stereo-multispectral endoscopic prototype in which a filter-wheel is used for surgical guidance to remove cholesteatoma tissue in the middle ear. Cholesteatoma is a destructive proliferating tissue. The only treatment for this disease is surgery. Removal is a very demanding task, even for experienced surgeons. It is very difficult to distinguish between bone and cholesteatoma. In addition, it can even reoccur if not all tissue particles of the cholesteatoma are removed, which leads to undesirable follow-up operations. Therefore, we propose an image-based method that combines multispectral tissue classification and 3D reconstruction to identify all parts of the removed tissue and determine their metric dimensions intraoperatively. The designed multispectral filter-wheel 3D-endoscope prototype can switch between narrow-band spectral and broad-band white illumination, which is technically evaluated in terms of optical system properties. Further, it is tested and evaluated on three patients. The wavelengths 400 nm and 420 nm are identified as most suitable for the differentiation task. The stereoscopic image acquisition allows accurate 3D surface reconstruction of the enhanced image information. The first results are promising, as the cholesteatoma can be easily highlighted, correctly identified, and visualized as a true-to-scale 3D model showing the patient-specific anatomy.Peer Reviewe

A framework for realistic 3D tele-immersion

Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite differ- ent from the experience of meeting face to face. We are abruptly aware that we are online and that the people we are engaging with are not in close proximity. Analogous to how talking on the telephone does not replicate the experi- ence of talking in person. Several causes for these differences have been identified and we propose inspiring and innova- tive solutions to these hurdles in attempt to provide a more realistic, believable and engaging online conversational expe- rience. We present the distributed and scalable framework REVERIE that provides a balanced mix of these solutions. Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic ex- periences to a multitude of users that for them will feel much more similar to having face to face meetings than the expe- rience offered by conventional teleconferencing systems

A Framework for Realistic 3D Tele-Immersion

Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite different from the experience of meeting face to face. We are abruptly aware that we are online and that the people we are engaging with are not in close proximity. Analogous to how talking on the telephone does not replicate the experience of talking in person. Several causes for these differences have been identified and we propose inspiring and innovative solutions to these hurdles in attempt to provide a more realistic, believable and engaging online conversational experience. We present the distributed and scalable framework REVERIE that provides a balanced mix of these solutions. Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic experiences to a multitude of users that for them will feel much more similar to having face to face meetings than the experience offered by conventional teleconferencing systems

A Framework for Realistic 3D Tele-Immersion

Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite different from the experience of meeting face to face. We are abruptly aware that we are online and that the people we are engaging with are not in close proximity. Analogous to how talking on the telephone does not replicate the experience of talking in person. Several causes for these differences have been identied and we propose inspiring and innovative solutions to these hurdles in attempt to provide a more realistic, believable and engaging online conversational experience. We present the distributed and scalable framework REVERIE that provides a balanced mix of these solutions. Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic experiences to a multitude of users that for them will feel much more similar to having face to face meetings than the experience offered by conventional teleconferencing systems

Provider Bulletin

RE: MassHealth Essential to Cover Visual Analysis by Optometrist

Short Paper Image-based Animation of Clothes

We propose a pose-dependent image-based rendering approach for the visualization of clothes with very high rendering quality. Our representation combines body-pose-dependent geometry and appearance. A geometric model accounts for low-resolution shape adaptation, e.g. animation and view interpolation, while small details as well as complex shading/reflection properties are accounted for through numerous images. Information on shading, texture distortion and silhouette at fine wrinkles are extracted from the images to allow later texture replacement. The image-based representations are estimated in advance from real samples of clothes captured in an offline process, thus shifting computational complexity into the training phase. For rendering, pose dependent geometry and appearance are interpolated and merged from the stored representations. Categories and Subject Descriptors (according to ACM CCS): I.3.8 [Computer Graphics]: Applications— 1

HILSMANN et al.: TEMPLATE-FREE SHAPE FROM TEXTURE 1 Template-free Shape from Texture with Perspective Cameras

This paper formulates the Shape-from-Texture (SFT) problem of deriving the shape of an imaged surface from the distortion of its texture as a single-plane/multiple-view Structure-from-Motion (SFM) problem under full perspective projection. As in classical SFT formulations we approximate the surface as being piecewise planar. In contrast to many methods, our approach does not need a frontal view of the texture or the texture elements as reference, as it optimizes 3D patch positions and orientations from transformations between texture elements in the image. The reconstruction results in minimizing a large sparse linear least squares cost function based on the reprojection error, a planarity constraint and the estimated rigid motion between patches. Texture element positions in the image are estimated under the assumption of a regular texture from clustered feature points representing repeating appearances in the image. We present results obtained with synthetic data as well as real data to evaluate our method.