Pedestrian Detection based on Improved Random Forest in Natural images

摘要：

an approach toward pedestrian detection applied to natural images using improved Random Forest (RF) is proposed. We take a more discriminative method for object part detection by applying the feature of pixel-based. We firstly train ? pedestrian random forest which directly maps the image patch appearance to the probabilistic vote about the possible location of the object centroid. For a testing image from the TUD dataset, our system requires four operations, which are feature extracting, passing patches through the trees, casting the votes, and processing the Hough images. Experimental results with the challenging TUD Image database demonstrate that the accuracy and robustness of our algorithm are better than those of ISM-based detection method, and this method is promising for object detection significantly.

关键词： Pedestrian Detection Natural Images Random Forest

作者: Wenshu Li Zhenxing Xu Song Wang Guobing Ma

作者单位: College of Informatics and Electronics,Zhejiang Sci-Tech University,Hangzhou,China

会议类型: 国际会议

会议名称: 2011 3rd IEEE International Conference on Computer Research and Development(ICCRD 2011)(2011第三届计算机研究与发展国际会议)

会议地点: 上海

会议语种:英文

页码: 468-472

在线出版日期: 2011-03-11（万方平台首次上网日期，不代表论文的发表时间）