Image Based Visual HullsTo Appear SIGGRAPH 2000
People
Goals Develop fast machine vision techniques for extracting geometry from
photographic input Visual Hull Overview Perhaps one of the most robust ways of extracting geometry from
photographic input is to use a space carving technique known as the visual hull. In this
approach, one first finds the silhouette contours of a foreground object in the images.
Each image region outside of the silhouette represents a region of space where the object
cannot be. These regions can be carved away. The resulting volume, called the visual hull,
is a conservative approximation to the actual geometry of the object. Object silhouettes
are often easy to detect in images, and these methods can be quite robust. Algorithm Out of a set of input images, fix one image as the reference image.
Each pixel in the reference image represents the view along a single line of sight in 3D.
This 3D line can be projected into one of the other images as a 2D line (see figure). This
is the well-known epipolar construction from the computer vision literature. One can
intersect this 2D line with the image regions occupied by the observed object. The result
is a set of “possibly occupied” intervals on the 2D line. These intervals can be
interpreted as “possibly occupied” intervals on the 3D line. The set of
intervals can be refined by projecting the 3D line into each of the other images as well.
The actual geometry can only reside in the intersection of the intervals computed using
all of the views. When this procedure is applied to all of the pixels in the reference
image, we have essentially constructed a visual hull. At each pixel, we have computed a
set of depth intervals in which the volume of the object must lie. This image-based visual
hull representation only requires a small quantity of floating point numbers to be stored
with each pixel, and it allows us to construct a visual hull at the resolution of the
input images. System Design
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