Intel® Threading Building Blocks (TBB) offers a rich and complete approach to expressing parallelism in a C++ program. It is a library that helps you take advantage of multi-core processor performance without having to be a threading expert. Threading Building Blocks is not just a threads-replacement library. It represents a higher-level, task-based parallelism that abstracts platform details and threading mechanisms for scalability and performance.
Synopsis: Homography transform in Fourier spectrum with application to object recognition. Ideally, recognition of objects should be projection, scale, translation and rotation invariant, just as they are in human vision. This, however, is a very complex problem, since numerous times an object is occluded and many objects rarely appear the same twice, due to different camera/observer positions, variable lighting or object motion. Our goal in this regard is to investigate autonomous object recognition in unconstrained environments by means of outlines of the objects, which we will refer to as the contours. One of the reasons for the popularity of contour-based analysis techniques is that edge detection constitutes an important aspect of shape recognition by the human visual system. The main motivation behind this work is that 2-D homography may overcome the problem of noise sensitivity and boundary variations.
MultiDrizzle automates and simplifies the detection of cosmic-rays and the combination of dithered observations using the Python scripting language and PyRAF, the Python-based interface to IRAF. MultiDrizzle was developed by the Science Software Branch at the Space Telescope Science Institute.
Image alignment is the process of matching one image called template (let's denote it as T) with another image, I (see the above figure). There are many applications for image alignment, such as tracking objects on video, motion analysis, and many other tasks of computer vision. In 1981, Bruse D. Lucas and Takeo Kanade proposed a new technique that used image intensity gradient information to search for the best match between a template T and another image I. The proposed algorithm has been widely used in the field of computer vision for the last 20 years, and has had many modifications and extensions. One of such modifications is an algorithm proposed by Simon Baker, Frank Dellaert, and Iain Matthews. Their algorithm is much more computationally effective than the original Lucas-Kanade algorithm.
This is code implements the example given in pages 11-15 of An Introduction to the Kalman Filter by Greg Welch and Gary Bishop, University of North Carolina at Chapel Hill, Department of Computer Science.
Delny is a Python package which can be used to make a Delaunay triangulation from a set of n-dimensional points. It is effectively a Python interface to libqhull, the C library of the Qhull program, but (currently) restricted to Delaunay triangulation. It was first developed to use in a mesh generator developed as dissertation at the University of Southampton with Hans Fangohr as supervisor. This very specific application area was the reason for the limited functionality of the libqhull wrapper, which in turn is likely the reason that there is useable code available.
The goal of the CGAL Open Source Project is to provide easy access to efficient and reliable geometric algorithms in the form of a C++ library. CGAL is used in various areas needing geometric computation, such as: computer graphics, scientific visualization, computer aided design and modeling, geographic information systems, molecular biology, medical imaging, robotics and motion planning, mesh generation, numerical methods... More on the projects using CGAL web page.