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This paper deals with motion capture of kinematic chains (e.g. humanskeletons) from monocular image sequences taken by uncalibrated cameras. Wepresent a method based on projecting an observation into a kinematic chainspace (KCS). An optimization of the nuclear norm is proposed that implicitlyenforces structural properties of the kinematic chain. Unlike other approachesour method does not require specific camera or object motion and is not relyingon training data or previously determined constraints such as particular bodylengths. The proposed algorithm is able to reconstruct scenes with limitedcamera motion and previously unseen motions. It is not only applicable to humanskeletons but also to other kinematic chains for instance animals or industrialrobots. We achieve state-of-the-art results on different benchmark data basesand real world scenes.

A Kinematic Chain Space for Monocular Motion Capture