Real-time augmented reality of user motion on mobile device using depth sensor

Nejc Škerjanc (2016) Real-time augmented reality of user motion on mobile device using depth sensor. MSc thesis.

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Abstract

People constantly aim to enhance the precision of the digital reconstruction of the real world. The detection and reconstruction of the human body does not provide comprehensive results with only RGB data stream. By introducing depth data flow from depth sensor we can create the reconstruction of our surroundings. The algorithm performs the detection of the human body with the intertwine of synchronous RGB and depth data stream. With the knowledge of physical rules of the human body proportions we can detect human body parts. With the results of the detection the application then draws an animated character (using sprite sheet) that covers as much as possible of the previously detected human body. The result is a library, which is written in the C++ programming language for a good transferability between platforms. Qualitative and quantitative analysis show that using synchronous RGB and depth data stream make the reconstruction more accurate and effective than using only RGB or depth data stream.

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