2,366 research outputs found
Single-image RGB Photometric Stereo With Spatially-varying Albedo
We present a single-shot system to recover surface geometry of objects with
spatially-varying albedos, from images captured under a calibrated RGB
photometric stereo setup---with three light directions multiplexed across
different color channels in the observed RGB image. Since the problem is
ill-posed point-wise, we assume that the albedo map can be modeled as
piece-wise constant with a restricted number of distinct albedo values. We show
that under ideal conditions, the shape of a non-degenerate local constant
albedo surface patch can theoretically be recovered exactly. Moreover, we
present a practical and efficient algorithm that uses this model to robustly
recover shape from real images. Our method first reasons about shape locally in
a dense set of patches in the observed image, producing shape distributions for
every patch. These local distributions are then combined to produce a single
consistent surface normal map. We demonstrate the efficacy of the approach
through experiments on both synthetic renderings as well as real captured
images.Comment: 3DV 2016. Project page at http://www.ttic.edu/chakrabarti/rgbps
Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging
The recovery of objects obscured by scattering is an important goal in imaging and has been approached by exploiting, for example, coherence properties, ballistic photons or penetrating wavelengths. Common methods use scattered light transmitted through an occluding material, although these fail if the occluder is opaque. Light is scattered not only by transmission through objects, but also by multiple reflection from diffuse surfaces in a scene. This reflected light contains information about the scene that becomes mixed by the diffuse reflections before reaching the image sensor. This mixing is difficult to decode using traditional cameras. Here we report the combination of a time-of-flight technique and computational reconstruction algorithms to untangle image information mixed by diffuse reflection. We demonstrate a three-dimensional range camera able to look around a corner using diffusely reflected light that achieves sub-millimetre depth precision and centimetre lateral precision over 40 cm×40 cm×40 cm of hidden space.MIT Media Lab ConsortiumUnited States. Defense Advanced Research Projects Agency. Young Faculty AwardMassachusetts Institute of Technology. Institute for Soldier Nanotechnologies (Contract W911NF-07-D-0004
Multiview photometric stereo
This paper addresses the problem of obtaining complete, detailed reconstructions of textureless shiny objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under changing illumination conditions. In contrast with previous photometric stereo techniques, ours is not limited to a single viewpoint but produces accurate reconstructions in full 3D. A number of images of the object are obtained from multiple viewpoints, under varying lighting conditions. Starting from the silhouettes, the algorithm recovers camera motion and constructs the object's visual hull. This is then used to recover the illumination and initialize a multiview photometric stereo scheme to obtain a closed surface reconstruction. There are two main contributions in this paper: First, we describe a robust technique to estimate light directions and intensities and, second, we introduce a novel formulation of photometric stereo which combines multiple viewpoints and, hence, allows closed surface reconstructions. The algorithm has been implemented as a practical model acquisition system. Here, a quantitative evaluation of the algorithm on synthetic data is presented together with complete reconstructions of challenging real objects. Finally, we show experimentally how, even in the case of highly textured objects, this technique can greatly improve on correspondence-based multiview stereo results
Optimal Radiometric Calibration for Camera-Display Communication
We present a novel method for communicating between a camera and display by
embedding and recovering hidden and dynamic information within a displayed
image. A handheld camera pointed at the display can receive not only the
display image, but also the underlying message. These active scenes are
fundamentally different from traditional passive scenes like QR codes because
image formation is based on display emittance, not surface reflectance.
Detecting and decoding the message requires careful photometric modeling for
computational message recovery. Unlike standard watermarking and steganography
methods that lie outside the domain of computer vision, our message recovery
algorithm uses illumination to optically communicate hidden messages in real
world scenes. The key innovation of our approach is an algorithm that performs
simultaneous radiometric calibration and message recovery in one convex
optimization problem. By modeling the photometry of the system using a
camera-display transfer function (CDTF), we derive a physics-based kernel
function for support vector machine classification. We demonstrate that our
method of optimal online radiometric calibration (OORC) leads to an efficient
and robust algorithm for computational messaging between nine commercial
cameras and displays.Comment: 10 pages, Submitted to CVPR 201
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