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Global scale integral volumes

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoComputer Vision - ECCV 2016 Workshops, Proceedings
KustantajaSpringer International Publishing
Sivut192-204
Sivumäärä13
Vuosikerta9913
ISBN (painettu)9783319466033
DOI - pysyväislinkit
TilaJulkaistu - 2016
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaEuropean Conference on Computer Vision -
Kesto: 1 tammikuuta 1900 → …

Julkaisusarja

NimiLecture Notes in Computer Science
Vuosikerta9913
ISSN (painettu)0302-9743
ISSN (elektroninen)1611-3349

Conference

ConferenceEuropean Conference on Computer Vision
Ajanjakso1/01/00 → …

Tiivistelmä

Integral volume is an important image representation technique, which is useful in many computer vision applications. Processing integral volumes for large scale 3D datasets is challenging due to high memory requirements. The difficulties lie in efficiently computing, storing, querying and updating the integral volume values. In this work, we address the above problems and present a novel solution for processing integral volumes for large scale 3D datasets efficiently. We propose an octree-based method where the worst-case complexity for querying the integral volume of arbitrary regions is O(log n), here n is the number of nodes in the octree. We evaluate our proposed method on multiresolution LiDAR point cloud data. Our work can serve as a tool to fast extract features from large scale 3D datasets, which can be beneficial for computer vision applications.

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