Illumination

The goal is to use a low-latency projector-camera system to intelligently illuminate only the portion of the scene where events are taking place. Unlike traditional lighting, the background is not illuminated resulting in high contrast image and video capture of the event.

The goal is to build vehicular headlight that can be programmed to perform many tasks with a single design to improve driver and traffic safety. Example tasks include producing glare free high beams, reducing visibility of rain and snow, improving visibility of the road and highlighting obstacles.

The goal is to build a smart vehicular headlight that can reduce visibility of rain and snow, making it less stressful and more safe for us to drive at night. This website describes the prototype built in 2011-2012.

The goal is to allow structured light system to capture dense shape information of highly textured objects in a single-shot.

The goal is to recover 3D shapes of complex objects using structured lighting that is robust to interreflections, sub-surface scattering and defocus.

We have built a structured light sensor for 3D reconstruction that works in sunlight using an off-the-shelf low-power laser projector.

By using precisely controlled valves and a projector-camera system, we create a vibrant, multi-layered water drop display. The display can show static or dynamically generated images on each layer, such as text, videos, or even interactive games.

We design a Projector-Camera system for creating a display with water drops that form planar and curved screens.

Our goal is to recover scene properties in the presence of global illumination. To this end, we study the interplay between global illumination and the depth cue of illumination defocus.

We present a framework for fast active vision using Digital Light Processing (DLP) projectors.

We have developed a detector to identify shadow boundaries on the ground in low quality consumer photographs.

We introduce a new, high-quality dataset of calibrated time-lapse sequences. Illumination conditions are estimated in a physically-consistent way and HDR environment maps are generated for each image.

Given a single outdoor image, we present a method for estimating the likely illumination conditions of the scene.

We analyze two sources of information available within the visible portion of the sky region: the sun position, and the sky appearance.