Knowledge Commons of Institute of Automation,CAS
Convolutional Neural Networks with Neural Cascade Classifier for Pedestrian Detection | |
Tong Bei(童贝)![]() ![]() ![]() ![]() | |
2016-10 | |
会议名称 | 全国模式识别学术会议(CCPR) |
会议日期 | 2016年11月 |
会议地点 | 四川省成都市电子科技大学图书馆求实厅 |
摘要 | The combination of traditional methods (e.g., ACF) and Convolutional Neural Networks (CNNs) has achieved great success in pedestrian detection. Despite effectiveness, design of this method is intricate. In this paper, we present an end-to-end network based on Faster R-CNN and neural cascade classifier for pedestrian detection. Different from Faster R-CNN that only makes use of the last convolutional layer, we utilize features from multiple layers and feed them to a neural cascade classifier. Such an architecture favors more low-level features and implements a hard negative mining process in the network. Both of these two factors are important in pedestrian detection. The neural cascade classifier is jointly trained with the Faster R-CNN in our unifying network. The proposed network achieves comparable performance to the state-of-the-art on Caltech pedestrian dataset with a more concise framework and faster processing speed. Meanwhile, the detection result obtained by our method is tighter and more accurate. |
关键词 | Convolutional Neural Network Cascade Classifier Faster R-cnn Pedestrian Detection |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/14472 |
专题 | 多模态人工智能系统全国重点实验室_机器人视觉 |
通讯作者 | Tong B(童贝) |
作者单位 | 中国科学院自动化研究所 |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Tong Bei,Fan Bin,Wu Fuchao,et al. Convolutional Neural Networks with Neural Cascade Classifier for Pedestrian Detection[C],2016. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
paper_45.pdf(1574KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论