—We present a generative model and inference algorithm for 3D nonrigid object tracking. The model, which we call G-flow, enables the joint inference of 3D position, orientation, ...
In this paper, we show how to estimate, accurately and efficiently, the 3D motion of a rigid or non-rigid object, and time-varying lighting in a dynamic scene. This is achieved i...
We present methods for learning and tracking human motion in video. We estimate a statistical model of typical activities from a large set of 3D periodic human motion data by segm...
Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black...
Generating vehicle trajectories from video data is an important application of ITS (Intelligent Transportation Systems). We introduce a new tracking approach which uses model-base...
Algorithms designed to estimate 3D pose in video sequences enforce temporal consistency but typically overlook an important source of information: The 3D pose of an object, be it r...