Project Morpheus

Introduction

Two decades ago, machine learning tasks related to images and videos were conducted by PhD scientists, and researchers from blue-chip companies, as the tasks relied on heavy resources and computational powers. Classifying a dog from a cat was a heavy and a major problem that many scientists worked on. But, currently, such a problem is a beginner-level task, as classifying images and videos have matured exponentially in the last 10 years.

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Challenge

Countless domains, ranging from agriculture to space travel, utilize Object Detection to great results. For many years, CCTV cameras have been just an eye that does not have a brain: the user has to analyze each frame by frame to obtain details from the footage; but nowadays, thanks to Artificial Intelligence, analysis of CCTV footage can be obtained almost instantly, and also at real-time too. Also, use-cases such as detecting spoilt cultivations, detecting obstacles in a self-driving car, automatically recognizing an employee from cameras are some places Object Detection has helped immensely.

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Solution

As with any AI project the first barrier of project Morpheus was also data. There was very little labeled open-source datasets available to track and detect game control postures such as punches and kicks. So we at rootcode labs took the initiative to create an action detection dataset internally by getting videos of our own Rootcoders making the postures and movements, these video streams were then split into frames and then labeled. The next step was to build the model, a combination of custom trained object detection and pose tracking models were used and finally to interface with the OS to input key presses our AI team developed several in house tools using C and C++. We are also in the process of releasing a research paper on the dataset and model we used to train this task.

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Impact

Although currently in the research stage, this application could revolutionize the future of gameplay as a whole, allowing gamers to control any first-person game based on their physical movement, without requiring an external peripheral in addition this would also lead gamers to be more active when playing games instead of being idle. Our vision for the secondary evolution of this project is to incorporate VR technology.