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Accelerator for Spatio-Temporal Video Filtering

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Spatio temporal filtering example where sparse flow vectors are converted to a dense flow-field (from).

Short Description

There are many image and video processing algorithms (e.g. calculation of Optical-Flow, or Image Domain Warps) that are usually solved using large optimization problems. The solution of such large optimization problems in real-time is difficult and sometimes even unfeasible. However, the mathematical structure of some of these problems allows us to approximate their solution by using non-linear filtering in the spatial and temporal domain. These filters scale better in terms of computational complexity than the corresponding optimization problems, and therefore would allow to perform certain video processing steps more efficiently.

In this project, we would like to implement the core parts of an efficient STEA filtering algorithm which has recently been developed in collaboration with Disney Research Zurich.

Status: In Progress

Scope: Semester or Master Thesis
Looking for 1-2 Interested Students
Supervisors: Michael Schaffner, Lukas Cavigelli


Introductory course in computer vision (optional)
Interest in computer graphics / computer vision
Matlab, VHDL and C++


10% Theory & Literature Study
20% Evaluations
70% Hw Architecture & ASIC Implementation


Luca Benini


Disney Research Zurich

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Detailed Task Description


Practical Details

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