PT Unknown
AU Victor Campmany
   Sergio Silva
   Antonio Espinosa
   Juan Carlos Moure
   David Vazquez
   Antonio Lopez
TI GPU-based pedestrian detection for autonomous driving
BT 16th International Conference on Computational Science
PY 2016
BP 2377
EP 2381
VL 80
DE Pedestrian detection; Autonomous Driving; CUDA
AB We 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.
ER