Pedestrian Detection Based on Improved HOG Feature and Robust Adaptive Boosting Algorithm

摘要：

Feature extraction and statistical classification methods are widely used in the object detection procedure. In this paper, improved Histograms of Oriented Gradients (HOG) features are used to represent the edge information of images. After that, HOG and Haar features are extracted to illustrate the performance of different types of features. Furthermore, the decision tree for classification is trained by Gentle Adaboost algorithm which selects some weak learners. Finally, we employ a novel detection method to get an outstanding and visual output. Experiments show that the improved method gets a good performance.

关键词： pedestrian detection HOG image processing gentle adaboost pattern classification

作者: Jiefa Wu Sheng Yang Lingling Zhang

作者单位: College of Information Science and Engineering Hunan University Changsha, Hunan, China

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 1556-1560

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）