The Tensor Voting Framework is a powerful technique for perceptual grouping, manifold learning, etc. It has proved to be a useful tool in the Computer Vision community. OpenTVF is an open source implementation of TVF.
PyCV is a Python package of modules useful for computer vision tasks. Its current focus is on boosting techniques, Haar-like features, and face detection. PyCV provides the world's fastest method for training a face detector, in a few hours.
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The STAIR Vision Library (SVL), originally developed to support the STanford AI Robot, provides software infrastructure for computer vision, machine learning, and probabilistic graphical models.
A photo gallery management system based on hand gesture recognition. You must make three color markers by yourself, which the red one on index of the right hand, the green one on thumb of the right hand and the blue one on index of the left hand.
The Vision Analysis Toolkit provides a framework for the development of computer vision algorithms using arbitrary named channel containers, flexible data types, and 1/2/3-D buffers.
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Horus is a toolkit to application development that includes inteligent agents. It provides some algorithm to computer vision; processing image; mapping, exploring and navigation of unknown environments; management of inteligent agent.
Diglo is a Music Information Retrieval System based on Computer Vision and Audio Spectrum Analysis, using algorithmic operations to find emergent patterns in musical performance. Also it functions as a low-cost Motion Capture Analysis system.
A set of interactive tools for studying, analyzing and learning Computer Vision techniques. Many algorithms implemented, with step by step execution, animations and interactive parameter modification, inside a multi-tabbed single window GTK interface.
proGPUKLT is a library for the Processing programming language and environment that wraps a GPU-implementation of the Kanade-Lucas-Tomasi feature tracker used for computer vision applications.
CVSharp (aka Computer Vision in C#) is a Computer Vision project. Until the present day just one part of the whole project was actually developed. It's called CVSharp Lab, an Image Processing Tool.
This program utilize the OpenCV (Intel Computer Vision) library to track an initial point over a series of frames. The image source is a camera or a pair of before/after pictures. Each frame passes some filter stages. This pipeline can be configured.
This Java native library wraps OpenCV (Computer Vision Lib.) function cvMatchTemplate and implements methods for utilities result visualization. It allows efficient images template matching using Normalized Cross-Correlation (NCC) and others algorithms.
Camera Kombat is an opensource fighting game based on computer vision that enables free, unencumbered interaction. In order to enable this level of interaction, images of the users are captured by a webcam and their gestures are recognized in real-time.
The free-vision project aims at creating a library for computer vision related functions, including camera capture interface, stereo, image processing, camera calibration and so on.
Proposed is an algorithm
that uses computer vision, combined with a modified Rubine classifier, to allow
arbitrary N-sided polygons as accepted sketches in real-time.
A tool for segmenting objects of interest in images, namely creating masks, and storing them for a set of images. It may provide some automatic/interactive segmentation for certain classes of objects. For computer vision / machine learning applications.
Myron (webcamxtra) brings native-implemented, cross-platform computer vision to Processing and Macromedia Director, allowing inexpensive commercial USB cameras to control just about anything. Keep computer vision easy and inexpensive for the people!
The Video Processing Evaluation Resource: A toolkit for evaluating computer vision algorithms on video, and a corresponding tool for annotating video streams with spatial metadata.
A C++ library of high level motion analysis/computer vision functions, coupled with GUIs that allow easy configuration and use. Current development focuses on color tracking, multiple camera calibration and triangulation, and 3D tracking algorithms.