NDLI: 3D keypoint detection by light field scale-depth space analysis

Content Provider	IEEE Xplore Digital Library
Author	Tosic, Ivana Berkner, Kathrin
Copyright Year	2014
Description	Author affiliation: Ricoh Innovations, Corp. Menlo Park, USA (Tosic, Ivana; Berkner, Kathrin)
Abstract	We present a method for 3D keypoint detection from light field data, typically obtained by planar camera arrays or plenoptic cameras. The proposed approach is based on construction of novel light field scale-depth spaces that are designed to leverage the specific properties of light fields. The constructed scale-depth spaces are based on a modified Gaussian kernel that is parametrized both in terms of scale of objects recorded by the light field and in terms of objects' depth. We prove theoretically that the new scale-depth space formulation and its spatial derivative satisfy the scale invariance property for all depths. By finding local extrema in such scale-depth spaces we locate 3D keypoints (such as 3D edges) and show that they outperform SURF keypoints on a 3D structure estimation task, both in accuracy and computational efficiency.
Starting Page	1927
Ending Page	1931
File Size	918530
Page Count	5
File Format	PDF
ISBN	9781479957514
DOI	10.1109/ICIP.2014.7025386
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-27
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three-dimensional displays Cameras Kernel Estimation Feature extraction Computer vision Image edge detection 3D keypoint detection Scale-space analysis light fields plenoptic cameras
Content Type	Text
Resource Type	Article

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