Search results for kenny mitchell

We present a system for rapid acquisition of bespoke, animatable, full-body avatars including face texture and shape.

We propose a novel pre-filtering method that reduces the noise introduced by depth-of-field and motion blur effects in geometric buffers (G-buffers) such as texture, normal and depth images.

In this paper, we propose a scalable method for streaming light€field video, parameterized on viewer location and time, that efficiently handles RAM-to-GPU memory transfers of light€field video in a compressed form, utilizing the GPU architecture for reduction of latency.

We present several mixed reality based remote collaboration settings by using consumer head-mounted displays, including an AR system linked with an AR system, a VR system with virtual body, a VR system without virtual body and a desktop computer.

We propose a new real-time temporal filtering and antialiasing (AA) method for rasterization graphics pipelines.

JUNGLE is an interactive, visual platform for the collaborative manipulation and consumption of nonlinear transmedia stories.

We propose an end-to-end solution for presenting movie quality animated graphics to the user while still allowing the sense of presence afforded by free viewpoint head motion.

We present a light field video synthesis technique that can achieve accurate reconstruction given a low-cost, widebaseline camera rig. Our system called, INDiuM, novelly integrates optical flow with methods for rectification, disparity estimation, and feature extraction, which we then feed to a neural network view synthesis solver with widebaseline capability. A new bi-directional warping approach resolves reprojection ambiguities that would result from either backward or forward warping only. The system and method enables the use of off-the-shelf surveillance camera hardware in a simplified and expedited capture workflow. A thorough analysis of the refinement process and resulting view synthesis accuracy over state of the art is provided.

This paper presents an approach to directly estimate an HDR light probe from a single LDR photograph, shot outdoors with a consumer camera, without specialized calibration targets or equipment.