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*************************************************************************** Updated 06/28/2018 The ezSift project has moved to https://github.com/robertwgh/ezSIFT *************************************************************************** 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...

...Almost any data from computer can be made into sense and included into project. N-Sense is modular by design, written mostly in c++ to allow optimal processing speed and uses OpenCv for Image/video processing. Target platforms are Linux, Android, Windows, Mac(starting from first). Project is not ready for public use yet. READ wiki before starting use software to avoid problems! NOTE: software causes brains to learn and change in long run and there is risk of many side effects like: headache, dizziness, increased intelligence, changes in music taste, change in perception of reality. ...

Welcome to Multimodal Unmanned Aerial Vehicle Controller (MMAR) This project intends to develop a multimodal interface which gives a human operator capability of controlling a QuadRotor UAV efficiently and more easily. During this project we use a simulated QuadRotor called AirRobot in a simulation environment for development of robots, USARSim. There are some aspects involved in this project including touch, pose tracking, gesture recognition, voice recognition, etc and we try to utilize capabilities of some devices available today such as Android Phones and Microsoft Kinect. ...

Welcome to Multimodal AirRobot Controller (MMAR) This project intends to develop a multimodal interface which gives a human operator capability of controlling QuadRotors efficiently and more easily. During this project we use simulated quadrotor called AirRobot in a simulation environment for development of robots, USARSim. There are some aspects involved in this project including touch, pose tracking, gesture recognition, voice recognition, etc and we try to utilize capabilities of devices available today such as some pose measurement tools like Android Devices (with accelerometer, compass, etc), some gesture recognizer like whether simple cameras or some other tools for instance Microsoft Kinect (with gesture and voice recognition), a Windows PC (As a Server for our application), another Windows PC (As a server to USARSim)