Increasing the Efficiency of GPU-Based HOG Algorithms Through Tile-Images

  • Darius MalysiakEmail author
  • Markus Markard
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9621)


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.


Image Composed image gpgpu High performance computing Histogram of oriented gradients HOG opencl Cuda 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Computer Science InstituteHochschule Ruhr WestMülheimGermany

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