Generalized Image Acquisition and Analysis

Computational Plenoptic Imaging

The plenoptic function is a ray-based model for light that includes the color spectrum as well as spatial, temporal, and directional variation. Although digital light sensors have greatly evolved in the last years, one fundamental limitation remains: all standard CCD and CMOS sensors integrate over the dimensions of the plenoptic function as they convert photons into electrons; in the process, all visual information is irreversibly lost, except for a two-dimensional, spatially-varying subset - the common photograph. In this state of the art report, we review approaches that optically encode the dimensions of the plenpotic function transcending those captured by traditional photography and reconstruct the recorded information computationally.

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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