Search Results for "alpha"

BoofCV is an open source Java library for real-time computer vision and robotics applications. Written from scratch for ease of use and high performance, it provides both basic and advanced features needed for creating a computer vision system. Functionality include optimized low level image processing routines (e.g. convolution, interpolation, gradient) to high level functionality such as image stabilization. Released under an Apache 2.0 license for both academic and commercial use.

The Fish4knowledge project investigated: information abstraction and storage methods for analyzing undersea video data (from 10E+15 pixels to 10E+12 units of information), machine and human vocabularies for detecting & describing fish, flexible process architectures to process the data and scientific queries and effective specialised user query interfaces. A combination of computer vision, database storage, workflow and human computer interaction methods were used to achieve this. The...

Computer Vision Application.

A library analog to those included in Matlab without the need of external libraries; just right for embedded or static linking. MTL was used to build a 3d Scanner. MTL consists of pars B - Basic Functions, Matrices, Images, Hypermodels (3d Models and up) N - Numeric Functions ranging from linear regression over nonlinear optimization to singular-value computation I - Image filters and Image enhancement H - Hardware related (optional part), does require additional libraries and is only...

According to the CBS news report, "if you use a computer more than two hours a day, you could be suffering from Computer Vision Syndrome (CVS)". The project's main objective is making a software that will help us protect our eyes from CVS.

Computer vision tracking module written in C++ as an extension to OpenCV, this code is the foundation for the "Are We There Yet?" installation by Ken Goldberg and Gil Gershoni in the Contemporary Jewish Museum Mar 31 - Jul 31 2011.

Java image viewer, an open source java learning application. Currently in alpha stage.

Igovision is an experimental project investigating applications of computer vision technology to the board game Go.

The Python Computer Vision Framework is an opened project deisgned for all those interested in computer vision. It aims at making computer vision more easy and structured and matlab-free. It may also be used for other artistic and scientific areas.

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.

A system intended for experimenting with computer vision algorithms employing OpenCL.

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.

Video processing and computer vision library for GNU/Linux offering interfaces to do image- and video-I/O with ImageMagick/Magick++, Xine, firewire digital camera (DC1394), and video for linux (V4L2). Note that this version of HornetsEye is deprecated. HornetsEye now is released as multiple packages on RubyGems.org. The source code is available on Github.com (see https://wedesoft.github.io/hornetseye-doc/ for more information).

Solving problems of counting the number of vehicles passing on a road during an interval time, as well as the problems of vehicles classification and estimating the speed of the observed traffic flow from traffic scenes acquired by a camera in real-time.

The CVR-Lib (Computer Vision and Robotics Library) is a C++ object oriented library for computer vision. It provides lots of functionality to solve mathematical problems, many image processing and analysis algorithms, classification tools, and much more.

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.

The Java parallel to the popular Intel computer vision library, OpenCV. OpenJCV = Open Java Computer Vision

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.

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.

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.

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.

IPA library is a platform developed for image processing and analysis. It composed by a lot of class of algorithms and functions with loose coupling, which can help users to develop professional applications of image processing or computer vision rapidly

The webcam computer vision (WCCV) project focuses on computer vision algorithms and systems that follow the web cam paradigm: cheap, robust and efficient. The project comprises designs, patterns, code, tutorials and examples.

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.