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Rucha Damle, Aditya Gurjar, Anuja Joshi, Kartik Nagre

Nowadays, Motion Sensing technology is increasingly deployed in many applications where human detection is required such as gaming, security and military. Motion sensing input device such as Microsoft’s Xbox 360 Kinect provides this applicability using infrared sensors. IR sensors are much more expensive compared to optical cameras with comparable resolutions and additional installation overheads, making it inconvenient to be widely used. Also inability to be used in mobile devices further limits its applicability. We create a system using OpenCV to be used as a library which will be used for human body skeleton detection and tracking. The proposed system uses video stream input through an integrated webcam and processes it to obtain human skeleton. The input video stream is processed frame by frame .All the major body joints are identified and tracked by the system using a combination of approaches like haar-training, blob detection, edge detection, optical flow tracking, and background subtraction. Skeleton model is developed using the obtained joints. Obtained skeleton is properly tracked to obtain real time results. Application developer will be able to include this library for use in his application and the system can be thus deployed without any sensors. Thus, the system provides the utility of Kinect-like devices easily with requirement of only normal camera in the device and thus will be easily made available. The system is developed with final aim of taking it on handheld devices like Smartphone, tablets etc.