Increasing the efficiency of gpu-based hog algorithms through tile-images

  • Object detection systems which operate on large data streams require an efficient scaling with available computation power. We analyze how the use of tile-images can increase the efficiency (i.e. execution speed) of distributed HOG-based object detectors. Furthermore we discuss the challenges of using our developed algorithms in practical large scale scenarios. We show with a structured evaluation that our approach can provide a speed-up of 30-180 % for existing architectures. Due to the its generic formulation it can be applied to a wide range of HOG-based (or similar) algorithms. In this context we also study the effects of applying our method to an existing detector and discuss a scalable strategy for distributing the computation among nodes in a cluster system.

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Metadaten
Author:Darius Malysiak, Markus Markard, Uwe Handmann
URL:https://link.springer.com/chapter/10.1007/978-3-662-49381-6_68
DOI:https://doi.org/https://doi.org/10.1007/978-3-662-49381-6_68
ISBN:978-3-662-49381-6
Parent Title (English):Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science
Publisher:Springer
Place of publication:Berlin
Document Type:Conference Proceeding
Language:English
Year of Completion:2015
Release Date:2019/07/03
Volume:2015
Issue:vol 9621
Pagenumber:13
First Page:708
Last Page:720
Institutes:Fachbereich 1 - Institut Energiesysteme und Energiewirtschaft
DDC class:600 Technik, Medizin, angewandte Wissenschaften / 621.3 Elektrotechnik, Elektronik
Licence (German):License LogoNo Creative Commons