G
Guido M. Schuster
Researcher at University of Applied Sciences of Eastern Switzerland
Publications - 49
Citations - 776
Guido M. Schuster is an academic researcher from University of Applied Sciences of Eastern Switzerland. The author has contributed to research in topics: Data compression & Lossy compression. The author has an hindex of 16, co-authored 48 publications receiving 748 citations. Previous affiliations of Guido M. Schuster include Northwestern University & USRobotics.
Papers
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Journal ArticleDOI
High spatio-temporal resolution video with compressed sensing.
Roman Koller,Lukas Schmid,Nathan Matsuda,Thomas Niederberger,Leonidas Spinoulas,Oliver Cossairt,Guido M. Schuster,Aggelos K. Katsaggelos +7 more
TL;DR: A prototype compressive video camera is presented that encodes scene movement using a translated binary photomask in the optical path, and the use of a printed binary mask allows reconstruction at higher spatial resolutions than has been previously demonstrated.
Journal ArticleDOI
A theory for the optimal bit allocation between displacement vector field and displaced frame difference
TL;DR: The fundamental problem of optimally splitting a video sequence into two sources of information, the displaced frame difference (DFD) and the displacement vector field (DVF) is addressed, and a general dynamic programming (DP) formulation which results in an optimal tradeoff between the DVF and the DFD is derived.
Proceedings ArticleDOI
Fast and efficient mode and quantizer selection in the rate distortion sense for H.263
TL;DR: A fast and efficient method for selecting the encoding modes and the quantizers for the ITU H.263 standard based on Lagrangian relaxation and dynamic programming (DP), which employs a fast evaluation of the operational rate distortion curve in the DCT domain and a fast iterative search which is based on a Bezier function.
Patent
Method and device for optimal bit allocation between different sources of information in digital video compression
TL;DR: In this paper, the authors present a method (200, 400) and device (500) for, within a variable or fixed block size video compression scheme, providing optimal bit allocation among at least three critical types of data: segmentation, motion vectors and prediction error, or DFD.
Journal ArticleDOI
Operationally optimal vertex-based shape coding
TL;DR: This article addresses the issue of operationally optimal shape encoding, which is a step in the direction of globally optimal resource allocation in object-oriented video and introduces the directed acyclic graph (DAG) formulation of the problem, which results in a fast solution approach.