Generalized Image Acquisition and Analysis

Intrinsic Shape Matching by Planned Landmark Sampling

Recently, the problem of intrinsic shape matching has received a lot of attention. A number of algorithms have been proposed, among which random-sampling-based techniques have been particularly successful due to their generality and efficiency. We introduce a new sampling-based shape matching algorithm that uses a planning step to find optimized "landmark" points. These points are matched first in order to maximize the information gained and thus minimize the sampling costs. Our approach makes three main contributions: First, the new technique leads to a significant improvement in performance, which we demonstrate on a number of benchmark scenarios. Second, our technique does not require any keypoint detection. This is often a significant limitation for models that do not show sufficient surface features. Third, we examine the actual numerical degrees of freedom of the matching problem for a given piece of geometry. In contrast to previous results, our estimates take into account unprecise geodesics and potentially numerically unfavorable geometry of general topology, giving a more realistic complexity estimate.

Teaching

Computational Optical Imaging

Lecture in winter term 2014/15

Lecturer: Ivo Ihrke

General Information

Course webpage - Libres Savoirs

When: 2014, Sept. 08th to 2014, Oct. 8th
Where: IOA/IOGS buiding room E202
Registration for mailing list: send email to Ivo Ihrke (firstname[dot]lastname[at]inria.fr)

Overview:

This lecture covers advanced digital imaging techniques for image correction and calibration, as well as algorithms and optical considerations for the extraction of three-dimensional content from (sets of) images. We explore the notion of computional-optical codesign and modern high-dimensional imaging techniques.

The tentative course schedule is


Monday 08.09.2014 Introduction and Recapitulation of Image Characteristics [pdf intro & recap]
Wednesday 10.09.2014 High Dynamic Range, Spectral, and Polarization Imaging [pdf hdr/spectral/polarization]
Monday 15.09.2013 Deconvolution [pdf deconvolution]
Wednesday 17.09.2013 Perspective Imaging and the Basics of 3D
Monday 22.09.2013 Structure-from-Motion
Wednesday 24.09.2013 Dense Stereo Techniques and Optical Flow
Monday 29.09.2013 Active 3D Scanning
Wednesday 01.10.2013 Tomography and Volumetric 3D
Monday 06.10.2013 Light Fields
Wednesday 08.10.2014 to be determined - possibly Compressed Sensing

FAQ:


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