 Energy Efficient Illumination and Imaging In this project we develop a light efficient method of performing transport probing operations like epipolar imaging. Our method enables structured light imaging to be performed effectively under bright ambient light conditions with a low power projector source. |
 Microcirculation Imaging and Analysis for Critical Care In this project, we develop real time tools to capture and analyze blood circulation in micro vessels that is important for critical care applications. The tools provide highly detailed blood flow statistics for bedside and surgical care. |
 Programmable Automotive Headlights 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. |
 Passive Tomography of Turbulence Strength This project explores an inexpensive method to directly estimate Turblence Strength field by using only passive multiview observations of a background. |
 Separating Texture and Illumination for Single-Shot Structured Light Reconstruction The goal is to allow structured light system to capture dense shape information of highly textured objects |
 Model Reducing Radiosity and Fluids of Deformable Scenes Novel mathematical framework to extend Galerkin projection to non-polynomial functions with applications to fast fluid simulation and radiosity rendering of deformable scenes. |
 Radiosity of Translucent Scenes The goal of the project is to efficiently render both the subsurface scattering of light within objects and the diffuse interreflections between them. |
 Fast Reactive Illumination through Rain and Snow (v1.0) 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. |
 Natural Human Pose Sampling using Spatial Hierarchy of Part Mixture Models David Marr inspired hierarchical model of part mixtures is used to sample natural looking human poses. The model is learned from a human image dataset and can be used to estimate human pose from a single test image. |
 Long range imaging through turbulence The project aims to model the optical turbulence through hot air and exploits the model to remove turbulence effects from images as well as recover depth cues in the scene. |
 Low-Power Structured Light in Sunlight We have built a structured light sensor for 3D reconstruction that works in sunlight using an off-the-shelf low-power laser projector. |
 Structured light 3D in the presence of Global Illumination The goal is to recover 3D shapes of complex objects using structured lighting that is robust to interreflections, sub-surface scattering and defocus. |
 Rectification and 3D Reconstruction of Deformed Documents The image of a deformed document is rectified by tracing the text and recovering the 3D deformation. |
 Vision for Efficient Vineyard Management Imaging and measurement of crop and canopy in vineyards. |
 AquaLux 3D: A Multi-Layered Display with Water Drops 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. |
 Flexible Voxels for Motion-Aware Videography We wish to build video cameras whose spatial and temporal resolutions can be adjusted post-capture depending on the motion in the scene. |
 Optimal Coded Sampling for Temporal Super-Resolution Multiple coded exposure cameras are used to obtain temporal super-resolution. |
 Globally optimal data-driven image distortion estimation The deformation field between a distorted image and the corresponding template is estimated. Global optimality criteria for the estimation are derived. |
 Ground Shadow Detector We have developed a detector to identify shadow boundaries on the ground in low quality consumer photographs. |
 (De)Focused Illumination and Global Light Transport 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. |
 Webcam Clipart 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. |
 Illumination estimation from a single outdoor image Given a single outdoor image, we present a method for estimating the likely illumination conditions of the scene. |
 Imaging through water We estimate the shape of the water surface and recover the underwater scene without using any calibration patterns, multiple viewpoints or active illumination. |
 Water drop Screens for Display We design a Projector-Camera system for creating a display with water drops that form planar and curved screens. |
 Reciprocal imaging using Illumination Masks We generalize dual photography for all types of light-sources using opaque, occluding masks. |
 [ Illustrating Motion through DLP Photography](./IM/procams webpage/motion%5Fillustrations.html) We process photographs taken under DLP lighting to either summarize a dynamic scene or illustrate its motion. |
 Temporal Dithering of Illumination We present a framework for fast active vision using Digital Light Processing (DLP) projectors. |
 What do the sun and sky tell us about the camera? We analyze two sources of information available within the visible portion of the sky region: the sun position, and the sky appearance. |
 Placement of cameras and sources in scattering media Optimal positioning of light sources and cameras for best visibility in impure waters. |
 Coplanar Shadowgram Imaging We present a practical approach to SFS using a novel technique called coplanar shadowgram imaging, that allows us to use dozens to even hundreds of views for visual hull reconstruction. |
 Novel Depth Cues from Uncalibrated Near-Field Lighting In this paper, we analyze what kinds of depth cues are possible under uncalibrated near point lighting. |
 Bone Reconstruction for Orthopedic Endoscopy We present a novel technique to reconstruct the surface of the bone by applying shape-from-shading to a sequence of endoscopic images, with partial boundary in each image. |
 Endoscopic Imaging We present a complete calibration of oblique endoscopes. |
 Frequency Space Analysis of Rain and Snow Removing rain and snow from videos using a frequency space analysis. |
 Legendre Fluids: Modeling and Rendering of Participating Media We present a unified framework for reduced space modeling and rendering of dynamic and non-homogenous participating media, like snow, smoke, dust and fog. |
 Surface Normal Clustering for Scene Analysis Scene points can be clustered according to their surface normals, even when the geometry, material and lighting are all unknown. |
 Acquiring Scattering Properties of Participating Media We have developed a simple device and technique for robustly estimating the properties of a broad class of participating media. |
 Single Scattering Model for Real-time Rendering We are interested in analyzing and rendering the visual effects due to scattering of light by participating media such as fog, mist and haze. |
 Structured Light in Scattering Media Laser range finding and photometric stereo in impure waters. |
 The Camera as a Weather Station Estimating visibility and weather condition from light source appearances. |
 Photometric Invariants We derive a new class of photometric invariants that can be used for a variety of vision tasks including lighting invariant material segmentation, change detection and tracking, as well as material invariant shape recognition. |
 Vision through Fog and Haze Models and algorithms for recovering scene properties from images captured in fog and haze. |
 Weather and Illumination Database (WILD) Calibrated and HDR time-lapse images of an outdoor scene for a year. |
 Assorted Pixels: Multidimensional Imaging This page describes a new technology developed at Columbia's Computer Vision Laboratory that can be used to enhance the dynamic range (range of measurable brightness values) of virtually any imaging system. |
We present the first comprehensive dataset and approach for powder recognition using multi-spectral imaging. By using Shortwave Infrared (SWIR) multi-spectral imaging together with visible light (RGB) and Near Infrared (NIR) and incorporating band selection and image synthesis, we conduct fine-grained recognition of 100 powders on complex backgrounds and achieve reasonable accuracy.
In this work, we propose a two-stage near-light photometric stereo method using circularly placed point light sources (commonly seen in recent consumer imaging devices like NESTcam, Amazon Cloudcam, etc). Because of the small light source baseline, the change of image intensity for the input image is small. In addition, in the near-light condition, the distant light assumption fails. So the light directions and intensities are not evenly distributed across the scene. Our proposed method tackles both issues.
A 2 parameter family of indirect light transport images captured live include short and long range indirect.
We develop a novel deep learning framework to simultaneously transform images across spectral bands and estimate disparity. A material-aware loss function is incorporated within the disparity prediction network to handle regions with unreliable matching such as light sources, glass windshields and glossy surfaces. No depth supervision is required by our method. To evaluate our method, we used a vehicle-mounted RGB-NIR stereo system to collect 13.7 hours of video data across a range of areas in and around a city. Experiments show that our method achieves strong performance and reaches real-time speed.
We propose an image formation model that explicitly describes the spatially varying optical blur and mutual occlusions for structures located at different depths. Based on the model, we derive an efficient MCMC inference algorithm that enables direct and analytical computations of the iterative update for the model/images without re-rendering images in the sampling process. Then, the depths of the thin structures are recovered using gradient descent with the differential terms computed using the image formation model. We apply the proposed method to scenes at both macro and micro scales.
We develop a method to estimate 3D trajectory of dynamic objects from multiple spatially uncalibrated and temporally unsynchronized cameras. Our estimated trajectories are not only more accurate and but also have much longer and higher temporal resolution than previous arts.
A new dataset that has 100 materials captured under under 12 different NIR lighting directions with 9 different viewing angles. A low-parameter BRDF model (in NIR) and fine scale geometry of surfaces are estimated simultaneously.
Capturing High-Speed Events with a Reactive Visual System 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.