Conservative Volumetric Visibility with Occluder Fusion

Visibility determination is a key requirement in a wide range of graphics algorithms. This paper introduces a new approach to the computation of volume visibility, the detection of occluded portions of space as seen from a given region. The method is conservative and classifies regions as occluded only when they are guaranteed to be invisible. It operates on a discrete representation of space and uses the opaque interior of objects as occluders. This choice of occluders facilitates their extension into adjacent opaque regions of space, in essence maximizing their size and impact. Our method efficiently detects and represents the regions of space hidden by such occluders. It is the first one to use the property that occluders can also be extended into empty space provided this space is itself occluded from the viewing volume. This proves extremely effective for computing the occlusion by a set of occluders, effectively realizing occluder fusion. An auxiliary data structure represents oc..

Sprite tree: an efficient image-based representation for networked virtual environments

International audienceIn this paper we present a pipeline for automatic analysis of neuronal morphology: from detection, modeling to digital reconstruction. First, we present an automatic, unsupervised object detection framework using stochastic marked point process. It extracts connected neuronal networks by fitting special configuration of marked objects to the centreline of the neurite branches in the image volume giving us position, local width and orientation information. Semantic modeling of neuronal morphology in terms of critical nodes like bifurcations and terminals, generates various geometric and morphology descriptors such as branching index, branching angles, total neurite length, internodal lengths for statistical inference on characteristic neuronal features. From the detected branches we reconstruct neuronal tree morphology using robust and efficient numerical fast marching methods. We capture a mathematical model abstracting out the relevant position, shape and connectivity information about neuronal branches from the microscopy data into connected minimum spanning trees. Such digital reconstruction is represented in standard SWC format, prevalent for archiving, sharing, and further analysis in the neuroimaging community. Our proposed pipeline outperforms state of the art methods in tracing accuracy and minimizes the subjective variability in reconstruction, inherent to semi-automatic methods

Realistic low-latency mobile AR rendering

When designing a system for mobile augmented reality, problems to be tackled concern tracking, rendering performance, end-to-end latency, battery usage, and communication bandwidth of the mobile platform. We developed an integral solution covering all these aspects, while still being manageable from the application's point of view. In this paper we outline the global layout of our system, and discuss a demo application projecting a statue on the campus