Welcome to the Dynamic Graphics Project lab of the University of Toronto

DGP, short for the Dynamic Graphics Project, is comprised of researchers spanning graphics, human-computer interaction, computer vision, and computational imaging. Founded in 1967, our group seeks to push the limits of perception, interaction, and visual communication in order to engage people with digital media in ways that have never been seen before. Our research has garnered multiple publication awards, academic fellowships and prizes, and even Academy Awards. Our alumni have become faculty at top universities throughout the world (e.g., Carnegie Mellon, Princeton, Virginia) and leaders at major industrial research labs (e.g., Adobe, Autodesk, Facebook/Meta, Google, Pixar).

Featured Research

Fluid Control with Laplacian Eigenfunctions

Physics-based fluid control has long been a challenging problem in balancing efficiency and accuracy. We introduce a novel physics based fluid control pipeline using Laplacian Eigenfluids. Utilizing the adjoint method with our provided analytical gradient expressions, the derivative computation of the control problem is efficient and easy to formulate. We demonstrate that our method is fast enough to support real-time fluid simulation, editing, control, and optimal animation generation. Our pipeline naturally supports multi-resolution and frequency control of fluid simulations. The effectiveness and efficiency of our fluid control pipeline are validated through a variety of 2D examples and comparisons. Click here to see the project page and paper.

Passive Ultra-Wideband Single-Photon Imaging

We consider the problem of imaging a dynamic scene over an extreme range of timescales simultaneously—seconds to picoseconds—and doing so passively, without much light, and without any timing signals from the light source(s) emitting it.

Because existing flux estimation techniques for single-photon cameras break down in this regime, we develop a flux probing theory that draws insights from stochastic calculus to enable reconstruction of a pixel’s time-varying flux from a stream of monotonically-increasing photon detection timestamps. We use this theory to (1) show that passive free-running SPAD cameras have an attainable frequency bandwidth that spans the entire DC-to-31 GHz range in low-flux conditions, (2) derive a novel Fourier-domain flux reconstruction algorithm that scans this range for frequencies with statistically-significant support in the timestamp data, and (3) ensure the algorithm’s noise model remains valid even for very low photon counts or non-negligible dead times.

We show the potential of this asynchronous imaging regime by experimentally demonstrating several never-seen-before abilities: (1) imaging a scene illuminated simultaneously by sources operating at vastly different speeds without synchronization (bulbs, projectors, multiple pulsed lasers), (2) passive non-line-of-sight video acquisition, and (3) recording ultra-wideband video, which can be played back later at 30 Hz to show everyday motions—but can also be played a billion times slower to show the propagation of light itself. Click here to see the project page and paper.

Home

Welcome to the Dynamic Graphics Project lab of the University of Toronto

Featured Research

Fluid Control with Laplacian Eigenfunctions

Passive Ultra-Wideband Single-Photon Imaging

News

Prof. Ahmed delivers keynote at PDC 2024

Adjunct Prof. Paul Dietz featured for his Animatronics Workshop

Profs. Ahmed and Chevalier receive tenure

DGP has strong showing at CHI 2024

Otman Benchekroun leads the first iteration of DGP Academy