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Pose Estimation is a general problem in Computer Vision where we detect the position and orientation of an object. … We address two problems: first, we establish an easy method for capturing and labeling 3D keypoints on desktop objects with an RGB camera; and second, we develop a deep neural network, called K e y P …
Analyzing human motion with high autonomy requires advanced capabilities in sensing, communication, energy management and AI. Wearable systems help us go beyond external cameras enabling motion analysis in the wild. However, such systems are still semi-autonomous. This is because, they require careful sensor calibration and precise positioning on the body over the course of motion. Moreover, these systems are plagued with bulky batteries and issues of time synchronization, sensor noise and drift. All of these restrictions hinder the use of wearable motion analysis in applications that rely on long-term tracking such as everyday gait analysis, performance measurement in the wild and full-body VR controllers. In this project, we aim to solve the specific problem of achieving autonomy and non-intrusiveness in wearable systems that target motion analysis. In order to do so, we extensively leverage efficient techniques in machine learning and systems design.