Broadly speaking, I am interested in all areas of computer graphics and computer vision. My work seeks to address the following high-level questions:
Computer Graphics: What powerful tools can we provide to artists, designers, scientists, and novice users for creating beautiful, expressive, artistic, and/or illustrative imagery and animation?
Computer Vision: How can we visually understand the world, extract meaning from images, and model the human visual system?
Moreover, I am interested in applications of Machine Learning to these two areas, as well as applications to Human-Computer Interaction.
Some specific research areas:
Painting and line drawing algorithms
How can we write computer software that helps in creating
artistic imagery and video? How can we enable computer animation in
the styles of human painting and drawing? Answering these questions
involves understanding aspects of artistic style and human
perception. We have developed technqiues for
painterly
rendering,
painterly
animation, and pen-and-ink illustration of 3D
surfaces.
Art, AI, Perception Essays
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The Science of Art | Can Computers Create Art? | Visual Indeterminacy | Why Do Line Drawings Work? |
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Computers Do Not Make Art |
Graphic Design and Data-Driven Aesthetics
Learning Human Motion Models from Data
How can we create virtual characters from live human performance? Doing so requires building computational models of human motion that incorporate physics of the body as well as an individual's style, explicitly or implicitly.
Our work in this area led to the first system for creating animation
by example, an area that has since become very popular in the
graphics community. We have developed
a real-time system for interactive character posing that uses machine learning to help determine
which poses are "most likely," and has been licensed to a major game
developer. More recently, we have developed some exciting new methods
for learning biomechanical human body models.
This method can predict how a person will move under
new circumstances, based on muscle strengths and stiffnesses estimated
from a motion capture sequence.
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Style machines | Style IK | Learning biomechanics | Motion Composition |
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Shared Latent Gaussian Processes | Gaussian Process Dynamical Models | Style-Content Gaussian Processes | Active learning for mocap |
Controllers for simulated locomotion
We are developing techniques for creating human and animal motor controllers that move in physically-realistic and expressive ways. Our work is inspired by insights from biology, robotics, and reinforcement learning.
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Prioritized Optimization | Optimizing Walking | Walking with Uncertainty | Feature-Based Controllers |
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Low-Dimensional Planning | Full-Body Spacetime | Rotational control | |
Person tracking and reconstruction from video
How do we perceive the 3D structure of a video sequence that contains
moving people and objects? We have developed several techniques that
address aspects of this problem, both addressing fundamental computer
vision questions, and also creating a practical application for
special effects. In one project, we have developed a method for
determining the 3D shape and motion of a non-rigid object from raw
video, without any prior knowledge about the deforming object.
This is based on our work on probabilistic non-rigid
structure-from-motion. We have developed a method for detailed reconstruction of a shaded 3D object from video, for diffusely-reflecting surfaces.
We have developed interactive tracking (rotoscoping) techniques that are now
in use in the special effects industry.
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Non-rigid SFM | Automatic non-rigid shape from video | Rotoscoping | Kinematic person tracking |
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Physics-Based Person Tracking | Hand reconstruction | Contact and dynamics estimation | |
Machine learning for geometry processing
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Surface Texture Synthesis | Learning body shape variation | Real-Time Curvature | Learning mesh segmentation |
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Furniture style | Metric Regression Forests | Learning segmentation from scraping | |
Virtual reality video and interfaces
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VR Video Editing | VR Video Review | Depth Conflict Resolution | VR Widgets |
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6-DoF VR video | View-Dependent VR Video | ||
Rigid shape reconstruction
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Smooth surfaces from video | Example-based photometric stereo | Example-based multiview stereo | Scanning with varying BRDFs |
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Image-Based Remodeling |
Image Understanding, Photo Editing, GANs
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Single-image deblurring | Image Sequence Geolocation | Acceptable photographic adjustments | Deep image tagging |
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Portrait Segmentation | GAN projection | GANSpace | |
Other machine learning and data science
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Segmental speech processing | Latent Factor Travel Model | Sparse Gaussian Processes | Event sequence visualization |
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Behance recommendations |