Liberovision Ag

Other

Eth Zuerich

Eth Zurich

Vizrt Ag

Remo Ziegler

Richard Keiser

Markus H Gross

Christoph Niederberger

Marcel Germann

Alexander Sorkine Hornung

Marc Stewart Levoy

Rolf Adelsberger

Tiberiu Popa

Stephan Wuermlin Stadler

Marcus Gross

Stephan Würmlin Stadler

Estimating a pose of an articulatedD object model () by a computer is done by &#x2022;obtaining a sequence of source images () and therefrom corresponding source image segments () with objects (14) separated from the image background; &#x2022;matching such a sequence () with sequences () of reference silhouettes ('), determining one or more selected sequences of reference silhouettes (&#x2032;) forming a best match; &#x2022;for each of these selected sequences of reference silhouettes (&#x2032;), retrieving a reference pose that is associated with one of the reference silhouettes (&#x2032;); and &#x2022;computing an estimate of the pose of the articulated object model () from the retrieved reference pose or poses. The result of these steps is an initial pose estimate, which then can be used in further steps, for example, for maintaining local consistency between pose estimates from consecutive frames, and global consistency over a longer sequence of frames.

Silhouette-based pose estimation

A computer-implemented method for estimating a pose of an articulated object model that is a computer basedD model of a real world object observed by one or more source cameras, including the steps of obtaining a source image from a video stream; processing the source image to extract a source image segment maintaining, in a database, a set of reference silhouettes, each being associated with an articulated object model and a corresponding reference pose; comparing the source image segment to the reference silhouettes and selecting reference silhouettes by taking into account, for each reference silhouette, a matching error that indicates how closely the reference silhouette matches the source image segment retrieving the corresponding reference poses of the articulated object models; and computing an estimate of the pose of the articulated object model from the reference poses of the selected reference silhouettes.

Method for estimating a pose of an articulated object model

What is disclosed is a computer-implemented image-processing system and method for the automatic generation of video sequences that can be associated with a televised event. The methods can include the steps of: Defining a reference keyframe from a reference view from a source image sequence; From one or more keyframes, automatically computing one or more sets of virtual camera parameters; Generating a virtual camera flight path, which is described by a change of virtual camera parameters over time, and which defines a movement of a virtual camera and a corresponding change of a virtual view; and Rendering and storing a virtual video stream defined by the virtual camera flight path.

Image processing method and device for instant replay

Using photographic flash for candid shots often results in an unevenly lit scene, in which objects in the back appear dark. A spatially adaptive photographic flash () is disclosed, in which the intensity of illumination () varies depending on the depth and reflectivity () of features in the scene. Adaption to changes in depth are used in a single-shot method. Adaption to changes in reflectivity are used in a multishot method. The single-shot method requires only a depth image (), whereas the multi-shot method requires at least one color image () in addition to the depth data ().

Spatially adaptive photographic flash unit

Growing community of inventors

Uster, Switzerland

Remo Ziegler