GPU-based Pedestrian Detection for Autonomous Driving

The authors propose a real-time pedestrian detection system for the embedded Nvidia Tegra X1 GPU-CPU hybrid platform. The pipeline is composed by the following state-of-the-art algorithms: Histogram of Local Binary Patterns (LBP) and Histograms of Oriented Gradients (HOG) features extracted from the input image; Pyramidal Sliding Window technique for foreground segmentation; and Support Vector Machine (SVM) for classification. Results show a 8x speedup in the target Tegra X1 platform and a better performance/watt ratio than desktop CUDA platforms in study.

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  • English

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  • Accession Number: 01605484
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jun 6 2016 10:02AM