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논문검색

Fast Pedestrian Detection with Adaboost Algorithm Using GPU

원문정보

Chong Chao Cai, Jue Gao, Bian Minjie, Peicheng Zhang, Honghao Gao

보안공학연구지원센터(IJDTA) International Journal of Database Theory and Application Vol.8 No.6 2015.12 pp.125-132
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초록

영어

Pedestrian detection is one of the hot research problems in computer vision field. The Cascade AdaBoost System is a commonly used algorithm in this region. However, when the training datasets become larger, it is still a time consuming process to build one Adaboost classifier. In this paper we detail an implementation of the AdaBoost algorithm using the NVIDIA CUDA framework based on the haar features as feature vectors, and downscaling with integral image. The result shows that we can get nearly 6x from the standard code to with our CPU implementation to achieve a near real-time performance and ensure better classification results in misjudgment.

목차

Abstract
 1. Introduction
 2. Feature Selection
 3. Adaboost Algorithm
 4. Achieve Adaboost Algorithm
 5. Experiment and Result
 6. Conclusions
 References

키워드

저자정보

  • Chong Chao Cai School of Computer Engineering and Science, Shanghai University, shanghai, China, Faculty of Information Technology, Huzhou Vocational & Technical College, Huzhou, Zhejiang, China
  • Jue Gao Computing Center, Shanghai University, Shanghai, China
  • Bian Minjie School of Computer Engineering and Science, Shanghai University, shanghai, China, Shanghai Shang Da Hai Run Information System Co., Ltd, Shanghai, China
  • Peicheng Zhang School of Computer Engineering and Science, Shanghai University, shanghai, China, Shanghai Shang Da Hai Run Information System Co., Ltd, Shanghai, China
  • Honghao Gao School of Computer Engineering and Science, Shanghai University, shanghai, China, Computing Center, Shanghai University, Shanghai, China

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