Generalized Image Acquisition and Analysis

Performance Capture of High-Speed Motion Using Staggered Multi-View Recording

We present a markerless performance capture system that can acquire the motion and the texture of human actors performing fast movements using only commodity hardware. To this end we introduce two novel concepts: First, a staggered surround multi-view recording setup that enables us to perform model-based motion capture on motion-blurred images, and second, a model-based deblurring algorithm which is able to handle disocclusion, self-occlusion and complex object motions. We show that the model-based approach is not only a powerful strategy for tracking but also for deblurring highly complex blur patterns.

Projects

Performance Capture of High-Speed Motion Using Staggered Multi-View Recording

Di Wu, Yebin Liu, Ivo Ihrke, Qionghai Dai, Christian Theobalt
Pacific Graphics 2012



Abstract

We present a markerless performance capture system that can acquire the motion and the texture of human actors performing fast movements using only commodity hardware. To this end we introduce two novel concepts: First, a staggered surround multi-view recording setup that enables us to perform model-based motion capture on motion-blurred images, and second, a model-based deblurring algorithm which is able to handle disocclusion, self-occlusion and complex object motions. We show that the model-based approach is not only a powerful strategy for tracking but also for deblurring highly complex blur patterns.
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Bibtex

@Article{Wu12,
author = {Di Wu and Yebin Liu and Ivo Ihrke and Qionghai Dai and Christian Theobalt},
title = {Performance Capture of High-Speed Motion Using Staggered Multi-View Recording},
journal = {Computer Graphics Forum},
volume = {31},
number = {7},
year = {2012},
pages = {2019--2028},
publisher = {Blackwell Publishing},
}
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