Perception-Based Illumination Information Measurement and Light Source Placement

The automatic selection of good viewing parameters is very complex. In most cases, the notion of good strongly depends on the concrete application. Moreover, when an intuitive definition of good view is available, it is often di#cult to establish a measure that brings it to the practice. Commonly, two kind of viewing parameters must be set: the position and orientation of the camera, and the ones relative to light sources. The first ones will determine how much of the geometry can be captured and the latter will influence on how much of it is revealed (i. e. illuminated) to the user. In this paper we will define a metric to calculate the amount of information relative to an object that is communicated to the user given a fixed camera position. This measure is based on an information-based concept, the Shannon entropy, and will be applied to the problem of automatic selection of light positions in order to adequately illuminate an object

Automatic Keyframe Selection for High-Quality Image-Based Walkthrough Animation Using Viewpoint Entropy

The computation of high quality animation sequences is expensive. Generation time for each frame can take a few hours. Recently, Image-Based Rendering methods have been proposed to solve this problem. As these techniques obtain new arbitrary views from precomputed ones at low cost, walkthroughs may be computed faster. Consequently, the selection of the precomputed images is a very important step. The initial set of keyframes should ful ll two requirements, it must be small but provide as much information as possible on the scene. In this paper we review several keyframe selection strategies and then we propose a new method based on entropy that achieve similar, and in some cases better, results

Optimized skin rendering for scanned models

Skin is one of the most difficult materials to reproduce in computer graphics, mainly due to two major factors: First, the complexity of the light interactions happening at the subsurface layers of skin, and second, the high sensitivity of our perceptual system to the artificial imperfections commonly appearing in synthetic skin models. Many current approaches mix physically-based algorithms with image-based improvements to achieve realistic skin rendering in realtime. Unfortunately, those algorithms still suffer from artifacts such as halos or incorrect diffusion. Some of these artifacts (e.g. incorrect diffusion) are especially noticeable if the models have not been previously segmented. In this paper we present some extensions to the Separable Subsurface Scattering (SSSS) framework that reduce those artifacts while still maintaining a high framerate. The result is an improved algorithm that achieves high quality rendering for models directly obtained from scanners, not requiring further processing

Visual analytics in histopathology diagnostics: a protocol-based approach

Computer-Aided-Diagnosis (CAD) systems supporting the diagnostic process are widespread in radiology. Digital Pathology is still behind in the introduction of such solutions. Several studies investigated pathologists' behavior but only a few aimed to improve the diagnostic and report process with novel applications. In this work we designed and implemented a first protocol-based CAD viewer supported by visual analytics. The system targets the optimization of the diagnostic workflow in breast cancer diagnosis by means of three image analysis features that belong to the standard grading system (Nottingham Histologic Grade). A pathologist's routine was tracked during the examination of breast cancer tissue slides and diagnostic traces were analyzed from a qualitative perspective. Accordingly, a set of generic requirements was elicited to define the design and the implementation of the CAD-Viewer. A first qualitative evaluation conducted with five pathologists shows that the interface suffices the diagnostic workflow and diminishes the manual effort. We present promising evidence of the usefulness of our CAD-viewer and opportunities for its extension and integration in clinical practice. As a conclusion, the findings demonstrate that it is feasibile to optimize the Nottingham Grading workflow and, generally, the histological diagnosis by integrating computational pathology data with visual analytics techniques