Markerless tracking of human pose is a hard yet relevant problem. In this paper, we derive an efficient filtering algorithm for tracking human pose at 4-10 frames per second using...
Varun Ganapathi, Christian Plagemann, Sebastian Th...
Abstract. We present a completely autonomous algorithm for the real-time creation of a moving subject’s kinematic model from optical motion capture data and with no a priori info...
Classifying and analyzing human motion from a video is relatively common in many areas. Since the motion is carried out in 3D space, the 2D projection provided by a video is somew...
Motion-based control is gaining popularity, and motion gestures form a complementary modality in human-computer interactions. To achieve more robust user-independent motion gestur...
Optical flow in monocular video can serve as a key for recognizing and tracking the three-dimensional pose of human subjects. In comparison with prior work using silhouettes as a ...