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An easy-to-use standalone SIFT library written in C/C++
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Updated 06/28/2018
The ezSift project has moved to https://github.com/robertwgh/ezSIFT
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The SIFT (scale-invariant feature transform) algorithm is considered to be one of the most robust local feature detector and description methods. Most of the open-source SIFT implementations rely on some 3rd-party libraries. Some of them even rely on a few different large libraries. These dependencies make the installation, compilation and usage not easy.
The ezSIFT library provides a standalone and lightweight SIFT implementation written in C/C++. ...
...The codebase supports building Heterogenous Command and Control Consoles and Accelerated User Attached Audiovisuals. The Command Centre Real Time Simulation Framework (under RT Linux) allows designers to build Fast Prototyped Consoles for advanced Simulations running on Local Area Networks.
Bundle of 2 softwares (extractor and merger).
Extractor broadcast skeletons and clouds to the merger. Multiple extractors can be set in a local network.
The merger holds transformation matrices for each extractor, allowing a efficient skeletons fusion from multiple point of view.
The merged skeletons are broadcasted in OSC.
This project is based on Melon: https://sourceforge.net/projects/kinect-melon/
[!] > requires OpenNI & NITE 1.5
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LBP implementation in multiple computing platforms (ARM,GPU, DSP...)
The Local Binary Pattern (LBP) is a texture operator that is used in several different computer vision applications and implemented in a variety of platforms. When selecting a suitable LBP implementation platform, the specific application and its requirements in terms of performance, size, energy efficiency, cost and developing time has to be carefully considered.
This is an augmented reality incarnation of a game called Spads and Fokkers, where 2 computer-generated 3d airplanes fight each other in the real world piloted by users thoughts. In this implementation AR and BCI tecnologies are used to make it possible.
Augmenting other natural interfaces namely handwriting, speech recognition to input Indian language characters to the computer. Speech synthesis is also provided to read out local language text.