Visual Computing

In contrast to existing systems that fabricate custom heads that are assembled to pre-fabricated plastic bodies, our system seamlessly integrates 3D facial data with a predefined figurine body into a unique and continuous object that is fabricated as a single piece.

Advances in 3D printing enable custom fabrication for a fraction of the traditional cost, opening new avenues for research and commercial enterprise. This talk presents a semi-automated system for fabricating figurines with faces that are personalized to the individual likeness of the customer.

We propose a novel density estimation technique that allows reusing sampled paths to reconstruct time-resolved radiance, and devise new sampling strategies that take into account the distribution of radiance along time in participating media.

This paper presents a controller for camera convergence and interaxial separation that specifically addresses challenges in interactive stereoscopic applications like games.

Recent advances in rendering and data-driven animation have enabled the creation of compelling characters with impressive levels of realism. While data-driven techniques can produce animations that are extremely faithful to the original motion, many challenging problems remain because of the high complexity of human motion.

We propose a novel density estimation technique that allows reusing sampled paths to reconstruct time-resolved radiance, and devise new sampling strategies that take into account the distribution of radiance along time in participating media.

We demonstrate our technique using rendered simulations and by 3D printing lens arrays, and we validate our approach in simulation with a user study.

In this paper, we expand the range of applications for content-aware weights to the multi-image setting and improve the quality of the recently proposed weights and the matching framework.

We present ratio tracking and residual tracking, two complementary techniques that can be combined into an efficient, unbiased estimator for evaluating transmittance in complex heterogeneous media.

We present a new approach to clothing simulation using low-dimensional linear subspaces with temporally adaptive bases. Our method exploits full-space simulation training data in order to construct a pool of low-dimensional bases distributed across pose space. For this purpose, we interpret the simulation data as offsets from a kinematic deformation model that captures the global shape of clothing due to body pose.