Fast Pedestrian Detection with Adaboost Algorithm Using GPU
Chong Chao Cai, Jue Gao, Minjie Bian, Peicheng Zhang, Honghao Gao · International Journal of Database Theory and Application · 2015
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.