VideoMan is a very easy image acquisition library. It is able to manage many video inputs at the same time, such as WDM Firewire and USB cameras, PointGrey cameras and video files. It can also render the inputs using OpenGL. Suitable for computer vision
This library implements the KLT Tracking algorithm [2004] for Feature Tracking in Video useful in computer vision tasks like object recognition, image indexing, tracking and structure from motion. This implementation uses programmable Graphics Hardware to achieve considerable speedup in the running time of the GPU-based implementation.
I would like to thank my advisor, Dr. A. Lynn Abbott, for helping me throughout
my research, Gary Fleming and the rest of the people at NASA Langley who provided all
the flight information and image sequences, and my parents who supported me in my
decision to enter graduate study. Also, thanks to Phichet Trisirisipal and Xiaojin Gong
for helping when I had computer vision questions, and Nathan Herald for his help
creating an illustration.
This library implements the KLT Tracking algorithm [2004] for Feature Tracking in Video useful in computer vision tasks like object recognition, image indexing, tracking and structure from motion. This implementation uses programmable Graphics Hardware to achieve considerable speedup in the running time of the GPU-based implementation.
The Kalman filter is an efficient recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements. It is used in a wide range of engineering applications from radar to computer vision, and is an important topic in control theory and control systems engineering. Together with the linear-quadratic regulator (LQR), the Kalman filter solves the linear-quadratic-Gaussian control problem (LQG). The Kalman filter, the linear-quadratic regulator and the linear-quadratic-Gaussian controller are solutions to what probably are the most fundamental problems in control theory.
David Vernon is the Coordinator of the European Network for the Advancement of Artificial Cognitive Systems and he is a Visiting Professor of Cognitive Systems at the University of Genoa. He is also a member of the management team of the RobotCub integrated working on the development of open-source cognitive humanoid robot.
Over the past 27 years, he has held positions at Westinghouse Electric, Trinity College Dublin, the European Commission, the National University of Ireland Maynooth, Science Foundation Ireland, and Etisalat University College.
He has authored two and edited three books on computer vision and has published over eighty papers in the fields of Computer Vision, Robotics, and Cognitive Systems. His research interests include Fourier-based computer vision and enactive approaches to cognition.
He is currently a Professor at Etisalat University College in Sharjah-United Arab Emirates, focusing on Masters programs by research in Computing fields.".[1]
VideoMan (Video Manager) is an open-source C++ library that helps you developing video based applications. We created VideoMan to increase our productivity developing computer vision applications, but it can be used in many other ways.
With VideoMan is very easy and fast to initialize any kind of video input like webcams, video files, frame grabbers, IEEE 1394 cameras and so on. You can initialize multiple inputs at the same time and show them in the screen. Also, you can show the results of the processing steps of your computer vision algorithm (extracted edges, back projections, detected blobs...) This way you can see the results of what are you coding, checking the results of your algorithm steps. Moreover, the implemented visualization scheme make easier to combine computer graphics with video, for example to show a 3d model on top of video for augmented reality applications.
sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step of every feature-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and motion (i.e. camera matrix) parameter estimates. Provided with initial estimates, BA simultaneously refines motion and structure by minimizing the reprojection error between the observed and predicted image points.
A sparse variant of the Levenberg-Marquardt algorithm implemented by levmar has been applied to bundle adjustment, a computer vision/photogrammetry problem that typically involves several thousand variables
