Dorian Chan

Holographic Illumination for Computer Vision Degree Type: CS
Advisor(s): Matthew O'Toole
Graduated: August 2025

Abstract:

Artificial illumination is ubiquitous in real vision systems. By coding extra information from a controlled light source into the images captured by a camera, so-called "active sensing" approaches robustly capture depth, reflectance and other visual cues crucial to tasks in robotics, manufacturing, consumer products and more. However, active sensors struggle with well-known challenges that lessen their practicality in modern systems. First, limited power in portable devices restricts range and outdoor performance of active sensors. Second, the slow speed of many active sensors precludes their usage for dynamic scenes. Finally,the lack of depth programmability in today's illumination sources reduces effective resolution in scenes with significant depth variation, and shrinks the space of potential future applications.

To tackle these challenges, this thesis explores using holographic illumination. Similar holographic systems have recently seen significant attention as displays in the augmented and virtual reality (AR/VR) literature. By combining a spatial-light modulator (SLM) with laser light, such devices can replicate natural 3D visual cues in a compact form factor, key aspects that are currently missing in modern AR/VR architectures.

In our work, we analyze how they can potentially be adapted as sources of active illumination. First, we show how holographic illumination can be used to build light-redistributive systems that allow for smarter energy usage in active sensing, enabling time-of-flight sensors with far-improved dynamic range. Next, we demonstrate how this light redistribution, when combined with the underlying fast speed of modern SLMs, allows for far faster projector systems, allowing for new types of triangulation light curtains. Finally, we test how the inherent coherent propagation of holographic illumination can be used to program meaningful, distinct content at multiple depths, enabling new user interfaces and depth-sensing methodologies.

Thesis Committee:
Matthew O'Toole(Chair)
Ioannis Gkioulekas
Aswin Sankaranarayanan
Mohit Gupta (University of Wisconsin-Madison)

Srinivasan Seshan, Head, Computer Science Department
Martial Hebert, Dean, School of Computer Science

Keywords:
Holographic illumination, active sensing, computer vision